Every descriptor should be formulated unambiguously. If a clear and unambiguous descriptor cannot be formulated, the term that is taken as a descriptor is supplied with a relator (a short label) or comment. In standards, there are special guidelines for introducing multiword descriptors (NISO 2005). The set of the thesaurus descriptors should be suffcient to describe the topics of the absolute majority of the documents in the domain. To explain why such thesauri are not suited for use in automatic document processing, we would like to provide several examples from the EUROVOC thesaurus (EUROVOC 1995). EUROVOC is created for 23 languages of the European Union and therefore it does not include Russian, but this thesaurus is one of the most well-known resources and therefore its principles are important to consider.

To improve the domain representation for humans, the guidelines for the creation of information retrieval thesauri often recommend not to include certain kinds of terms in a thesaurus (infrequent terms, terms that are too specifc, similar terms etc.; United Nations 2009). Relying on human indexers, traditional information retrieval thesauri try to limit the inclusion of ambiguous terms, which leads to problems in automatic document processing. In EUROVOC, for example, the single-word term *bank* is presented in only one sense; other senses are described in form of multiword terms (*sperm bank, data bank, blood bank*). Note, that in WordNet, the word *bank* has ten senses as a noun and eight senses as a verb. In the defense category, EUROVOC does not contain such terms as *soldier* or *military force*; only the descriptor *armed force* is presented.

The relations in information retrieval thesauri are quite different from WordNet-like lexical relations. Information retrieval thesauri have a small set of generalized relations, which are usually subdivided into two classes: hierarchical and associative. The most frequent type of hierarchical relations between preferred terms in information retrieval thesauri are the broader-narrow relations (BT and NT relations), comprising class-subclass, instance-class, and sometimes part-whole relationships. The associative relations convey various other types of domain-specifc relations between concepts (related term (RT) relation). The standards and manuals on thesaurus development formulate principles for representing associative relations as the most signifcant ones (NISO 2005; Aitchinson and Gilchrist 1987).

The RT relations are considered to be symmetric, but looking at the existing thesauri, it is possible to see that this is not true in many cases. For example, in EUROVOC the *air transport* descriptor has RT relations with such descriptors as *air law*, *air traffc control*, and *aviation fuel*, which are much narrower than the *air transport* descriptor. This simple system of relations has been criticized in many works (Tudhope et al. 2001) but it has an important advantage: it can be applied to any domain without additional efforts to develop the detailed set of domain-specifc relations, which always is a very complex task.

In Russia, the most known information retrieval thesauri are developed in the Institute of Scientifc Information of Russian Academy of Sciences (INION RAN). This institution publishes separate issues of thesauri on economics, sociology, linguistics, and so on, created according to the guidelines of international and national standards on thesaurus construction. These thesauri also cannot be used for automatic processing of document and news fows (Mdivani 2013).

## 18.3 RuThes Structure, Units, and Relations

#### *18.3.1 RuThes General Structure*

In the construction of RuThes, both popular paradigms for computer thesauri were used: concept-based units, a small set of relation types, and rules for including multiword expressions as in information retrieval thesauri; languagemotivated units, detailed sets of synonyms, and description of ambiguous words as in wordnets. Also, some issues of ontology research—for example, concepts as main units, strictness of relation description, necessity for manystep inference—are accounted for (Guarino 1998, 2009).

RuThes is a hierarchical network of concepts. Each concept has a name, relations with other concepts, and a set of language expressions (words, phrases, terms) whose meanings correspond to the concept. The whole set of RuThes' concepts is subdivided into general lexicon and sociopolitical thesaurus. *General Lexicon* comprises general concepts and words that can be met in various specifc domains such as *sozdanie* (creation), *udalit'* (remove), *uslovnye* (conditional). *Sociopolitical Thesaurus* contains thematically oriented lexemes and multiword expressions as well as domain-specifc terms of the broad sociopolitical domain. The whole RuThes thesaurus includes more than 60,000 concepts and more than 200,000 Russian text entries (words and expressions). The published version of RuThes for use in noncommercial applications includes 110,000 text entries (RuThes 2019).

The *sociopolitical domain* is the domain of problems, relationships, and situations of the contemporary society (Loukachevitch and Dobrov 2015). Subdomains of the sociopolitical domain are themselves large domains such as economics, law, or international relations, each with its own terminology. However, the specifc feature of the sociopolitical domain (and its subdomains) is that most domain terms are known to nonprofessionals. Here, in the sociopolitical domain, the general language and domain terminologies adjoin and mix with each other. At present, the RuThes sociopolitical thesaurus includes terminology from such domains as politics, elections, sociology, demography, social security, civil and criminal law, the court system, banking, security, economics (including macroeconomics, industry, agriculture, and transport), ecology, accidents, sports, culture, and others.

#### *18.3.2 RuThes Units*

The RuThes thesaurus is a hierarchy of concepts viewed as units of thought. A concept is associated with the set of language expressions that refer to it in texts. This approach is similar to approaches of traditional information retrieval construction (NISO 2005). In most cases, concepts should have denotational distinctions from related concepts. Such distinctions can be expressed in a specifc set of relationships or associated language expressions: *text entries*.

Words and phrases whose meanings refer to the same concepts represented in the thesaurus are called ontological synonyms. Ontological synonyms can comprise sense-related words belonging to different parts of speech (i.e., *privatizaciâ* [privatization] *vs. privatizirovat'* [to privatize]); in contrast to traditional terminological resources and information retrieval thesauri that contain mainly nouns or noun phrases. A thesaurus for automatic document processing should contain various types of language units. Also, language expressions relating to different linguistic styles, technical terms, and lexical units can be presented as ontological synonyms related to the same concept. For example, the concept *Oil industry* has the following text entries: *neftânaâ promyšlennost'* (oil industry)—neutral, *neftânka*—slang, *nefteprom*—abbreviation. Compositional multiword expressions may be included into synonymic sets as well. Each concept should have a clear, univocal, and concise name. Such names often help to express and delimit the denotational scope of the concept. In addition, the concepts' names can be used in the analysis of the results of automatic document analysis, for example in visualization of trends or as cluster names.

Ontological synonyms, variants of lexical units, and technical terms (Nazarenko and Zargayouna 2009) are collected specially. After a concept has been introduced, an expert searches for all possible synonyms or orthographic variants, single words, and phrases that can be associated with it. These synonymic sets can also include multiple variants of the references to the same concept. For example, the concept *Ohrana prirody* (Nature protection) is associated with almost 50 different text entries in Russian, for example *zasita* ̂ *prirody* (defense of nature)*, sohranenie prirody* (maintenance of nature), *zasis*̂ *at'* ̂ *prirodu* (to protect nature), *sohranât' prirodu* (to maintain nature), and others. These variants are useful to describe in the thesaurus because they directly refer to their concept. Besides, multiword term variants often contain ambiguous words within themselves. Thus, the inclusion of such term variants decreases the overall lexical ambiguity and facilitates disambiguation. All variants are collected during the analysis of real texts, usually news articles, legislative acts, or domain-specifc documents.

In fact, the introduction of such a concept as *Nature protection* corresponds more to information retrieval thesauri than wordnets, because one of the important principles of WordNet-like resources is to include single words and lexicalized phrases into synsets (Bentivogli and Pianta 2004; Maziarz and Piasecki 2018). The phrase *nature protection* seems compositional, but the concept *Nature protection* is signifcant for the contemporary life of the society and it has relations with other important concepts of the sociopolitical domain.

As can be seen, one of the diffcult issues in developing application-oriented resources, such as wordnets or information retrieval thesauri is the inclusion of units (synsets or descriptors) based on the senses of multiword expressions, for example noun compounds (Bentivogli and Pianta 2004). Manuals and standards for information retrieval thesaurus development provide detailed principles for multiword term selection (NISO 2005; Aitchinson and Gilchrist 1987). In RuThes, the introduction of concepts based on multiword expressions is not restricted but encouraged if this concept adds some new information to the knowledge described in the thesaurus (Loukachevitch and Lashevich 2016).

#### *18.3.3 RuThes Relations*

Conceptual relations in the thesaurus may be utilized for several purposes, including query expansion in information retrieval, clustering related concepts mentioned in a text as a basis for better recognition of the main theme and subthemes in the document, and disambiguation of ambiguous terms and lexical units. Working with such a broad scope of concepts, we utilize a set of relations that can be applied to concepts in various domains, in contrast to domain-dependent relations.

RuThes has a small set of conceptual relations consisting of four main relations that describe the most important links of a concept. In fact, the current set of relations in the thesaurus is a more ontologically motivated variant of classic inter-descriptor relationships in information retrieval thesauri, which usually include hierarchical relations, such as broader term (BT) and narrower term (NT), and associative relations—related term (RT).

The frst relation of RuThes is *the class-subclass relation* as it is treated in ontological approaches (Guarino 1998; Gangemi et al. 2003). To establish such relations, we apply tests similar to those used in ontology development. The tests are directed toward avoiding incorrect use of class-subclass relations and not mixing them up with other types of relations (such as type-role relation, class-instance relation), because errors in relation types degrade logical inference (Gangemi et al. 2003). The class-subclass relationship is considered as a transitive relation with the inheritance property.

The second relationship is *part-whole relation*, which is established using specifc ontological restrictions (Gangemi et al. 2003). Our decision on partwhole relations is based on the following principles:

Part-whole relations in RuThes comprise such relationships as parts of physical objects, territorial and geographical parts, process parts, and others (see examples in Table 18.1). Also, some other relationships are presented as partwhole relations in RuThes: an attribute and its bearer, a role or a participant in the situation (Winston et al. 1987, 27–28), entities and situations in the encompassing sphere of activity (Table 18.1).

In such a broad scope, part-whole relations described in RuThes are close to the so-called *internal relations* (parthood, constitution, quality inherence, and participation) as described by Guarino (2009). At the same time, part-whole relations in RuThes have a very important restriction (correlating with the information retrieval thesauri guidelines about the necessity to describe only inherent properties as hierarchical relations [NISO 2005]): a concept-part should be related to its whole during the normal existence of its instances: the so-called *ontological dependence*.

To analyze the ontological dependence between entities *X* and *Y*, it is necessary to determine whether entity *X* can exist by itself or whether its existence depends on the existence of *Y*. We describe the following types of dependent parts in RuThes:

**Table 18.1** Types and examples of part-whole relations in RuThes

Thus, we put existential constraints on the part-whole relations in RuThes. These constraints do not change the transitivity of part-whole relations if it was postulated. The inference mechanism can thereby utilize the transitivity of part-whole relations and rely on the chain of part-whole relations (Guizzardi 2011; Loukachevitch and Dobrov 2015).

The fnal types of relationships are *nonsymmetrical and symmetrical associations*, which are subdivided from the symmetric related term (RT) relation of conventional information retrieval thesauri. The nonsymmetrical associations are established on the basis of the ontological dependence of concepts. Symmetrical associations are described in the very restricted number of cases.

Associative relationships (RT relations) are quite common in information retrieval thesauri; they are established to provide additional links between descriptors for use in the indexing or retrieval of documents (NISO 2005). Such relations in information retrieval thesauri are always considered as symmetrical; however, many associative relations found in published thesauri demonstrate the evident absence of symmetry, for example *illness*—*disease prevention*, *illness*—*sick leave* (EUROVOC), et cetera. The frst term in each pair is much more general than the other one.

Considering the problems involved in formalizing traditional information retrieval thesauri to adapt them to the contemporary level of ontological research, some authors propose changing the thesaurus's traditional system of relations to a formalized set of predicates and to provide axioms for such a set (Soergel et al. 2004). However, in creating such multidomain resources as RuThes, it is very diffcult to fnd the universal set of semantic relations and apply them consistently. Therefore, we substituted the traditional thesaurus relation of symmetric association with another quite generalized relation, which can be applied in many various domains. We usually refer to this relation as a nonsymmetrical association, *asc*1–*asc*2. The defnition of this relation is again based on a variant of ontological dependence, the so-called *external dependence* in ontological terms (Gangemi et al. 2003; Guarino 2009). This relation is established between two concepts *c*1 and *c*2 when two requirements are fulflled:

**Table 18.2** Examples of conceptual dependence relations denoted as nonsymmetrical associations in RuThes

These two conditions mean that the concept *c*2 (dependent concept) externally depends on *c*1 : *asc*1(*c*2,*c*1) = *asc*2(*c*1,*c*2). Table 18.2 presents some examples of conceptual relationships, where conceptual dependence can be seen.

Relations of ontological dependence are applicable to various domains; therefore, they are usually used in top-level ontologies (Gangemi et al. 2003). An additional advantage of using these relations in thesauri for automatic document processing is their usefulness for describing links between a concept based on the sense of a compositional multiword expression and concepts corresponding to the components of this multiword expression. As a result, a multiword-based concept (e.g., *Automobile racing*) is described as the dependent concept and its component concept (*Automobile*) as the main concept. This allows us to introduce concepts based on various types of multiword expressions and to establish their necessary relations.

## 18.4 Description of Social and Political Concepts in RuThes

The specifc part of RuThes called Sociopolitical thesaurus provides detailed coverage of thematic lexical units and terms in the broad sociopolitical domain of contemporary written Russian (mainly news articles, laws, and offcial documents). The thesaurus was utilized in document-processing applications within information,retrieval and information analytical systems (Loukachevitch and Dobrov 2015). Every project gave the opportunity to improve the descriptions of lexical senses, reveal useful expressions, and add domain terms of new subdomains of the sociopolitical domain, which, in turn, improved the description of related lexical senses.

Let us consider several examples of recently introduced concepts related to popular topics discussed in the Russian and international press and their descriptions in RuThes. Figure 18.1 represents the description of concepts

**Fig. 18.1** Representation of the current international sanctions situation in the thesaurus form

related to sanctions: *Sankcii protiv Rossii* (Sanctions against Russia), *Sankcionnaâ vojna* (War of sanctions), *Sankcionnaâ produkciâ* (Products under sanctions). The upper-left form enumerates a list of concepts in alphabetical order.

The left-lower form shows Russian text entries for the concept *War of sanctions* such as *vojna sankcij* (war of sanctions) and *sankcionnaâ vojna* (sanctions war). The right-upper form presents the relations of the highlighted concept. Figure 18.1 shows the relation of the *War of sanctions* concept with such concepts as *Meždunarodnyj konfikt* (International confict), *Antisankcii* (Countersanctions), and *Meždunarodnye sankcii* (International sanctions). In particular, the *War of sanctions* concept is described as dependent from the concept *International sanctions*, because it could not appear without this concept. The *Counter-sanctions* concept is described as a part of *War of sanctions.* The lowerright form shows Russian text entries for the related concept *Antisankcii* (Counter-sanctions). They include: nouns (*antisankcii, kontrsankcii*), noun groups (*otvetnye sankcii* [sanctions as an answer]), and adjectives (*antisankcionnyj, kontrsankcionnyj*).

After the pension reform in Russia was announced in 2018, new concepts *Predpensioner* (Person before retirement age) and *Predpensionnyj vozrast* (Before retirement age) were introduced in the thesaurus. These concepts appeared in Russian law to provide social security to some categories of the population in relation to raising the retirement age. The *Before retirement age* concept is described as a part (property) of *Person before retirement age* according the thesaurus guidelines. The concept *Person before retirement age* depends on the concepts *Pensioner* and *Pension system* because it requires their existence.

An innovation of the Russian transport law introduced yellow boxes on roads, a specifc kind of road marks (box marking). In Russian, the concept is called *Vafel'naâ razmetka* (literally, *waffe marking*). The concept's set of Russian text entries includes word *vafel'nica*, which previously meant only "waffe iron," a kitchen appliance for baking waffes. Therefore, the new sense of the word *vafel'nica* and new multiword expression *vafel'naâ razmetka* have been added into RuThes.

In recent years, cryptocurrencies were actively discussed. The corresponding concepts: *kriptovalûta* (cryptocurrency), *èlektronnye den'gi* (electronic money), *Bitcoin*, *kriptomat* (Cryptocurrency ATM machine) have been introduced into the thesaurus.

Thus, RuThes provides detailed coverage of thematic lexical units and terms in the broad sociopolitical domain of contemporary written Russian (mainly news articles, laws, and offcial documents). The thesaurus can be used as a conceptual indexing tool in information analytical systems. RuThes can also be a useful instrument for developing knowledge-based categorization systems in conditions when a training collection for machine learning methods is absent and cannot be easily created. It is possible because the thesaurus contains thousands of words and expressions stored in a hierarchical structure, which can be used in the description of categories for automatic text categorization (Loukachevitch and Dobrov 2015).

## 18.5 RuThes as <sup>a</sup> Source for Russian WordNet

Despite the fact that RuThes is currently published for noncommercial use, people would like to have a large Russian wordnet. Therefore, a transforming procedure from the published version of RuThes (RuThes-lite) to the largest Russian WordNet (RuWordNet 2019) has been initiated. One of the most distinctive features of WordNet-like resources is their division into synset nets according to parts of speech. Therefore, all text entries of RuTheslite were subdivided into three parts of speech: nouns (single nouns, noun groups, and preposition groups), verbs (single verbs and verb groups), adjectives (single adjectives and adjective groups). We have obtained 29,297 noun synsets, 12,865 adjective synsets, and 7636 verb synsets. The divided synsets were linked to each other with the relation of part-of-speech synonymy.

The hyponym-hypernym lexical relations (hyponymy shows the relationship between a generic term [hypernym] and a specifc instance of it [hyponym]) were established between synsets of the same part of speech. These relations include direct hyponym-hypernym relations from RuThes-lite. In addition, the transitivity property of hyponym-hypernym relations was employed in cases when a specifc synset did not contain a specifc part of speech, but its parent and child had text entries of this part of speech. In such cases, the hypernymy-hyponymy relation was established between the child and the parent of this synset.

Other RuThes relations were modifed. The part-whole relations from RuThes were semi-automatically transferred and corrected according to traditions of WordNet-like without the expanded set of part-whole relations. Some part-whole relations were transformed to domain relations, for example *zavod* synset (industrial plant) is related to the domain *promyšlennost'* (industry) via the domain relation. The ontological dependence relations of RuThes were manually transformed to appropriate semantic relations such as antonyms, cause, entailment, and some others. RuWordNet is publicly available (RuWordNet 2019).

## 18.6 Conclusion

In this chapter, we described the RuThes thesaurus that was created as a linguistic and terminological resource for automatic document processing in Russian. In the construction of RuThes, both popular paradigms for computer thesauri were used: concept-based units, a small set of relation types, and rules for including multiword expression as in information retrieval thesauri; language-motivated units, detailed sets of synonyms, and description of ambiguous words as in wordnets. A large part of RuThes is devoted to the description of terms and concepts related to the current sociopolitical life in Russia and in the world—the so-called Sociopolitical thesaurus.

We have supported the development of RuThes for many years by introducing new concepts, representing new senses, and recording multiword expressions. In this chapter, we have showed some examples of representing newly appeared concepts related to important internal and international events. We demonstrated how we used the thesaurus' relation system for describing these concepts. Hence, we consider RuThes as a kind of formalized encyclopedia of social and political life of the contemporary society.

## References

*of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*, 2259–2268.

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

## Social Media-based Research of Interpersonal and Group Communication in Russia

*Olessia Koltsova, Alexander Porshnev, and Yadviga Sinyavskaya*

## 19.1 Introduction

Social media and, in particular, social networking sites (SNS) have become an important source of research data both in Russia and worldwide which, correspondingly, has given rise to new research methods and approaches. Social media data serve as sources of two major types of data: frst, the data about the "offine" reality, such as migration, electoral outcomes or mental disorders, and second, the data about human behavior within social media, which includes online self-presentation, networking, media consumption or purchasing behavior. Russian social media, unusual both in terms of their market confguration and data access opportunities, create a slim, but an interesting stream of research.

In this chapter, we critically review the most exemplary works in Russian social media studies. Our goal is to discuss strengths and weaknesses of different research designs and methods that are seldom reported in the papers focused on the research results. As of now, Russian social media studies can be classifed along two major lines. The frst line differentiates between studies using Russian SNSs as a source of data about human behavior in general, and those that aim at studying specifcally Russian society or Russian-speaking community with the data from different social media, including the Russian SNSs.

The second line of differentiation is disciplinary, and we can single out three disciplines that have contributed most to Russian social media research:

O. Koltsova • A. Porshnev • Y. Sinyavskaya (\*)

Higher School of Economics (HSE University), Saint Petersburg, Russia

<sup>©</sup> The Author(s) 2021 335

D. Gritsenko et al. (eds.), *The Palgrave Handbook of Digital Russia Studies*, https://doi.org/10.1007/978-3-030-42855-6\_19

psychology and health studies, sociology and political science. The latter has focused specifcally on Russia, and especially on the relations between social media and protests. Sociology has addressed a wide range of topics, such as virtual demography, education and ethnic relations whose results refect specifc Russian context, but can often be extrapolated beyond the Russian society. Psychological research has mostly contributed to fundamental psychology by studying the relation of social media to such universal psychological phenomena as depression or personality traits. Health studies may be situated between psychology and sociology.

This review chapter focuses on the three above-mentioned disciplines. We fnd that they use a wide range of data types and data-collection techniques: self-reported data (from surveys and experiments collected off-line or on-line) and SNS activity user data (incl. user texts and their metadata, such as timestamps and geolocation, the data from group accounts, data on links between accounts and various external statistics). Methods of data analysis vary from traditional discourse analysis and classical statistics to social network analysis (SNA), supervised and unsupervised machine learning, and various combinations of those.

We should also note that Russian social media are actively used in computational linguistics. Though this research community works with the Russian language, it does not focus either on the Russian society or a broader Russianspeaking community, tackling such problems as optimization of information retrieval, text clustering and summarization, named entity recognition or automatic translation. It thus forms a distinct stream of literature addressed in this book (for more, see Chaps. 26, 19, 29, 25, 23 and 24) that we leave out in this review. We also omit the large and important topic of "research ethics is social media studies" as it is a subject for a separate contribution.

The rest of the chapter is structured as follows. First, we briefy introduce the context of social media development in Russia and show how it has resulted in their unique position within the global SNS landscape. The next three sections are devoted to the disciplinary overviews of political science, sociology, health and psychology. We conclude with summarizing both research opportunities and limitations created by social media.

## 19.2 Social Media in Russia

Russian Internet landscape is unique in terms of its "home-grown" character. According to Forbes.ru, Russian companies compete with global players nearly in all spheres of Internet business, including search engines, mailing services and social media (Forbes.ru 2019). Unlike in China, where the closed Internet ecosystem owes most of its success to the policy of technical, political and economic isolation known as the Great Chinese Firewall, Russian information technologies (IT) industry has until recently developed without any protectionist barriers.

**Table 19.1** SNS use in Russia according to media research (October 2018, in mil)

a Active user: user who wrote at least one public message per month

bMessage: any publicly available post—status, wall post or comment, post or comment in online group etc. The analysis did not include private messages

As a result, social media "diets" of Russian and Russian-language users are substantially different from global trends (see Table 19.1). Social networking site VKontakte (VK), a Russian replica of Facebook, has by far higher reach and especially higher user activity than all other SNSs, followed by popular, but much less active Odnoklassniki. Facebook (FB) in Russia is a niche network that attracts higher-educated audiences oriented towards international integration, business and, to some extent, more oppositional political views (e.g. Enikolopov et al. 2018). VK, on the other hand, has become a universal tool for everyday communication, practical task-solving and small business. A typical VK user consumes news from a few large entertainment and/or political public pages run by media organizations and also belongs to a multitude of smaller groups that include everything from school classes and self-help communities to pages of local businesses that use VK to promote their services.

Consequently, political and market pressures experienced by VK are to some extent different from those faced by Facebook. Unlike Facebook, VK has not been accused of illegitimate infuence on elections, since it is widely accepted that electoral outcomes in Russia depend on very different things (Gel'man 2014). Combined with relatively low importance of privacy among the Russian population (Kisilevich et al. 2012), this until recently has been creating incentives for VK to privilege data sharing over privacy protection. As a result, the amount and diversity of data available through VK application programming interface (API) is incomparably higher than in FB, and thousands of business and research actors use it on a daily basis. It is this unique data availability that has made possible such large-scale virtual demography projects as Webcensus (Zamyatina and Yashunsky 2018) (see further below). Surprisingly, such opportunities have attracted nearly no attention from international scholars, which is why most VK-based research has been done by Russian researchers.

Another important trend is the fragmentation of the Russian-speaking online environment. For a while, VK was an integrating medium for Russian-speakers on the Post-Soviet space, but this capacity has been severely hindered by the ban of VK in Ukraine in 2017 and the overall deterioration of Russia's relations with the rest of the world. It is plausible to expect that in the near future comparative studies that include Russia might be increasingly dominated by research based on global SNSs which will decrease the value of VK as a data source.

## 19.3 Political Science

Political science research on social media is the largest among the three mentioned disciplines. It focuses on a number of subfelds, such as the role of social media for political protest and civil activity (Enikolopov et al. 2018; Koltsova and Selivanova 2019), mapping political discourses and agendas formed both by lay and professional SNS users, including media professionals and politicians (Bodrunova et al. 2018; Goncharov and Nechay 2018; Bulovsky 2019; Kelly et al. 2012; Koltsova and Koltcov 2013) or topic-specifc political discussions (Filer and Fredheim 2016), and the newly emerged topic of SNS-channeled propaganda (Barash and Kelly 2012; Kelly et al. 2012; Stukal et al. 2017; Badawy et al. 2018; Sanovich 2017).

Studies based on discourse, agenda and discussion mapping are by their nature, mostly descriptive; and when based on manual text analysis only, usually not scalable. However, manual approach can be enhanced with automated text analysis, albeit in such case often at cost of its depth. Goncharov and Nechay (2018) beneft from applying such a combination to a collection of about 45 thousand tweets related to the anti-corruption protests organized by a prominent Russian oppositionist Alexei Navalny in spring 2017. To evaluate the mobilization potential of Twitter, they apply keyword-determined timeconstrained sampling and then use topic modeling to reveal content-based clusters and social network analysis (SNA) to fnd link-based communities. They convincingly demonstrate the dominance of an oppositional and a loyalist metacluster in both partitions. An important methodological note of the authors is that hashtags seldom occur in their data, which questions the frequently used hashtag-based sampling in Twitter research. At the same time, the authors do not specify the type of links used, neither they explain how the two partitions of their data are related. Most importantly, they do not fnd an answer for their main question about mobilization effect of Twitter, since cluster analysis is a method suitable for descriptive, not for inferential investigation.

This limitation is shared by most SNS research based on clustering techniques and some research based on manual coding. Thus, Koltsova and Koltcov (2013) illustrate the growth of political topics at the expense of other topics in the Russian-language LiveJournal (LJ) top blogs on the eve of the Russian parliamentary elections in 2011 which, nevertheless, does not lead to any hypothesis testing. Bodrunova et al. (2018) go further by formulating the hypotheses about prevalence of certain media roles among professional authors of tweets discussing politicized violent events in four different countries, including Russia. Tweets are classifed manually; in principle, automatically clustered tweets might have equally been tested for prevalence, but no statistical procedures for doing so have been introduced in this research. The authors, nevertheless, offer a multitude of interesting details that help understand the structure of the political discussion in the four countries in a comparative perspective, which is still quite rare in quantitative media studies. In particular, they echo with Goncharov and Nechay (2018) in observing that Russian media on Twitter, unlike those of other countries, cluster along the pro-government anti-government axis.

A successful attempt to do inferential research based on blog texts is presented by Bulovsky (2019). He fts a regression model to fnd out the difference between Twitter communication used by authoritarian and democratic political leaders across 144 countries, including Russia. He fnds that the former have a signifcantly lower number of posts per day and a signifcantly smaller proportion of replies to other users.

Another diffculty with SNS research is a possible lack of context and the reliability of non-SNS-based data. Enikolopov et al. (Enikolopov et al. 2018) perform a most rigorous statistical inference to evaluate the infuence of VK on protests in Russia using the data on the large rallies against electoral fraud and on voting in the electoral cycle of 2011–2012. They fnd out that, paradoxically, VK penetration increases pro-government voting in the respective cities, but simultaneously has a positive effect on both the probability of protests and the number of protesters. There is not enough data to test possible alternative explanations of this effect, such as a polarizing infuence of higher SNS penetration levels on the population. At the same time, the reliability of both voting data (given the unknown character of electoral fraud) and the protest data (given that they were taken from the media where the numbers reported by the protesters and by the police dramatically diverged) is highly questionable. Reuter and Szakonyi (2015), who use offine survey data only, obtain somewhat different results and fnd that the usage of international social networks Twitter and Facebook increased the awareness about electoral fraud, while the usage of domestic VK and Odnoklassniki did not.

Koltsova and Selivanova (2019) solve the problem of contextual enrichment of SNS data with the deep involvement of one of the researchers into the social movement they study. Similar to Goncharov and Nechay (2018), their goal is to evaluate the mobilization potential of VK communities. In particular, they study the effect of VK on the turnout of the movement activists at the poll stations in the role of independent observers on the voting day in 2014. As the movement created VK groups responsible for each of the 17 administrative districts in St. Petersburg, the researchers investigate them all and fnd that their size, activity and density are positively related to the overall turnout; however, offine observers are neither more active nor more connected members of online groups. The authors offer two alternative interpretations of this effect, based on their experience with the movement, still the problem of reliability of the offine turnout data is one of the unresolved issues.

Importantly, SNS data, though more "objectifed" than self-reported or hand-coded data, are not always reliable either. Comparing Twitter discussions devoted to two resonant political murders in Russia and Argentina, Filer and Fredheim (2016) fnd out that a signifcant proportion of the Russian tweets, unlike Argentinean messages, are automatically generated (2016, 13). This has two implications: frst, the value of Twitter as the data source in Russian political research is limited because of the network's limited penetration. Second, the study of Filer and Fredheim leads us to a whole range of related research topics that include online state propaganda, fake news, bot-generated content, infuence of all those factors on electoral outcomes and the problem of the use of personal SNS data for political purposes.

Of this stream of research, Russia-related research has a number of special features. First, some research on political propaganda is performed as bot detection (Stukal et al. 2017). However, not all bots are political (some are commercial), and not all propaganda is robotized (some is manual). Second, the phenomena that researchers try to trace—for example, trolls—are hard to defne conceptually and even harder to fnd empirically. For instance, Badawy et al. (2018) perform an interesting descriptive research of a collection of tweet accounts identifed as Russian "trolls." Using one of the algorithms of automatic classifcation known as label propagation, they identify most trolls as conservative-leaning, while Botometer software (botometer.iuni.iu.edu/#!/) (another classifcation algorithm) allows them to determine that the majority of those who retweeted trolls were not bots. Those valuable fndings are to a certain extent limited by the data used. While trolls are defned as "malicious accounts created for the purpose of manipulation" (Badawy et al. 2018, 258) that is, intentionally deceptive—the authors use a list of Twitter accounts taken from the website of the US congress Committee for Intelligence via a publication at the www.recode.net website. The list contains only Twitter IDs and usernames, and no other information is searchable. It is thus unclear whether the list creators followed the authors' defnition of trolls, and if so, how they learnt about users' purposes. More broadly, fnding empirical referents for concepts whose defnitions are based on intention (e.g. deception) is a challenge, while taking out intention from the defnition of political trolls deprives them from their core meaning and makes them lumped together with authors of unconventional, still legitimate opinions.

Third, this type of research is sometimes not entirely free from politicization. For instance, Sanovich (Sanovich 2017) refers to Barash and Kelly (2012) and Kelly et al. (2012) as the research that for the frst time identifed a "largescale deployment of pro-government bots and trolls in Russia" in favor of President Medvedev. However, this is not exactly what the sources suggest. First of all, while the word "bot" is mentioned only once, "troll" is never mentioned in either of the sources. Second, Barash and Kelly (2012) show unusual distributions of activity around tweets related to Medvedev's innovation policy program, while Kelly et al. (2012), using the same data, note that the whole "innovation cluster" of tweets disappears when they flter out "instrumental" accounts—those that are likely to use search engine optimization (SEO) and automation (bots). The authors do not offer any interpretations, but this suggests that accounts that tweeted about innovation were likely to use commercial promotion methods, in particular automation. Since Kollanyi et al. (2016) show that automation was spread both among pro-Trump and, to a lesser extent, pro-Clinton Twitter accounts during the 2016 US electoral campaign, such accounts might be equally termed trolls. However, there is more sense in distinguishing between trolls and bots than placing them in one category. This does not mean that the Russian government has never used trolls but suggests a certain lack of accuracy when it comes to the Russian computational propaganda research.

To sum up, social media data may signifcantly enrich the repertoire of research in the feld of political science in Russia by providing access to large volumes of data and thereby conducting large-scale research with the usage of automated methods of data analysis. In particular, the access to textual and network data makes it possible to grasp the substance of political discussions and track communication fows between different political parties. At the same time, the results of such research should be viewed through the lens of existing technical and methodological constraints. First, often accessible data allows producing only a limited range of conclusions, for example, descriptive ones. Different approaches to the conceptualization of key concepts which sometimes leads to inconsistent results are also of highly relevant issue. Finally, online data from social media are not free from specifc limitations which may affect its reliability.

## 19.4 Sociology

#### *19.4.1 Virtual Demography and Structure*

The relative openness of VK data has enabled a number of large-scale studies investigating VK population structure, composition and patterns of communication. By far the largest of them is the project "Virtual population of Russia" (Zamyatina and Yashunsky 2018). It is based on the analysis of approximately 200 million VK accounts and 3.5 billion friendship links, although only 88 million accounts have been found to claim their location in Russia. The most valuable outcome of this project is an interactive website webcensus.ru that contains various subsets of the initial sample at different levels of aggregation and visualizes the most important distributions in the form of charts and maps. The data include age, gender, education, friendship patterns, migration routes and others, along with their relations, for example, distribution of average friendship connectedness over the Russian regions. This data is an incredible resource for researchers seeking to assess the difference of their samples from the total VK population of Russia and thus to statistically test various hypotheses about specifc features of the studied sub-populations. Russia is, to our knowledge, the only country for which such detailed virtual census exists. However, this data has a serious limitation: it dates back to 2015 and, as such data collection is extremely expensive and is unlikely to be updated.

Some studies aim at restoring missing data in SNS accounts based on the available data from other accounts. Such data may include age, gender, geolocation and others. As this research mostly lies in the sphere of computer science, we omit it here, with an exception of two related papers based on the full VK data from the Russian city of Izhevsk. The frst paper studies the impact of missing geolocation data on the features of the city friendship network (Kaveeva and Gurin 2018), while the second does the same in relation to fake accounts (Kaveeva et al. 2018). In the frst paper, the authors train a classifer that restores users' city of residence based on the accounts in which this data is present. They fnd out that while the city friendship network grows substantially when the missing users are added, most of its important metrics, do not change, while modularity and the number of communities in the largest connected component experience a very modest growth. This suggests that using incomplete data based on the users who choose to report publicly is a valid research strategy in social network analysis. In the second paper the authors train a classifer to recognize fake accounts. After deleting them, friendship network experiences the reverse change, as compared to the frst paper, that is modularity and the number of communities drop a little. One limitation of the second paper is the nature of its training set that is based on self-reported data from 32 users who were asked to assess their friends. The problem of fake account identifcation is close to troll and bot detection and has no easy solution as all these types of accounts mutate quickly in their attempts to imitate real users.

Other research devoted to SNS structural features attempts inferential design (Kisilevich et al. 2012; Rykov et al. 2018). Kisilevich et al. (2012) examine how age and gender are related to the amount of disclosed information, based on 16 million accounts from a Russian SNS My World (Moj Mir, www. my.mail.ru). This research allows not only to evaluate the completeness of selfreported user data but also to investigate their self-disclosure behavior. The authors report that self-disclosure dramatically drops with age, but fnd no substantial gender difference which, as they claim, differentiates the Russian SNS users from the Western users. However, the statistical procedure used to claim no gender difference is somewhat unclear, while the presented plots suggest that females may be less frequently sharing information about their political views but are more often sharing quite a number of other types of information.

#### *19.4.2 Social Issues and Problems: Education, Ethnicity, Urbanity*

While virtual demography and related studies are interested in the online population per se, various research tackling more specifc sociological topics uses SNS data to obtain results about offine reality, or about the role of SNS in the respective problem or issue, be it education, migration, ethnic relations, or urbanity.

For instance, Smirnov (2018) uses VK data on 4400 Russian students to predict their scores in Programme for International Student Assessment (PISA) test—an international test assessing learning outcomes in reading, mathematics and science among 15-year old students. He obtains the data on 73 thousand online communities which students belong to and reaches the correlation of about 0.5 between the predicted and the real PISA scores. The most interesting conclusion is that groups contributing most to high scores are related to arts and science, while those contributing to low scores are related to humor, sex and horoscopes. Although 0.5 is a high correlation in social science, it also means that VK group membership cannot be used as the only predictor of PISA scores. Since VK group membership cannot be used as a causal explanation of PISA performance either, the signifcance of such type of research should be treated with caution. In general, the predictive power of such models tends to drop the more the farther in time other studied datasets are from the original dataset.

Alexandrov et al. (2018) use VK self-reported geolocation data to study factors infuencing outgoing educational migration. They examine a larger number of student migration destinations over a sample of 85 thousand VK users aggregated at the city level. They fnd that, quite predictably, Far East and Southern Siberia are gravitated to China, North-West—to the Nordic countries, and Muslim regions—to the Middle East. It is interesting that among signifcant predictors they fnd both offine factors, such as religious and geographic proximity, and online factors, such as the number of VK groups related to the country of destination in the donor city. However, of course, it is unknown how well self-reported data on users' secondary schools and universities refect the overall educational migration fows. This poses a broader question of the extent to which online data represent offine reality.

Ethnicity has been another important topic in Russia as a multi-ethnic society, with studies asking how communication in social media either refects ethnic tensions or infuences ethnic relations. Bodrunova et al. (2017) study the posts of top LiveJournal bloggers to determine how different ethnic groups are treated. They frst extract ethnicity-related topical clusters via topic modeling and then hand-code 30 most relevant texts in each of 33 ethnicity-related clusters. Among other things, they fnd that Central Asians are treated as relatively positive aliens, with North Caucasians being presented both as negatively assessed aliens and aggressors. But while North Caucasians are also sometimes victimized, Americans are always both negative and aggressive, which suggests that global political conficts overshadow local inter-ethnic tensions. This research is one of the few addressing the problem of instability of topic modeling by running the algorithm several times and choosing only stable topics, which is virtually never done in empirical social research. However, it has problems with representativity both in terms of the size of the coded sample and in terms of the choice of LiveJournal popular bloggers as a source.

Urban studies is a subfeld that is widely believed to beneft from social media data. However, it often results in the simple plotting of social media data on geographical city maps that, unlike the mapping of political discussions or virtual demography, is often less useful. Human movement in urban spaces is much better detected with mobile phone data than with social media data, and the content or sentiment of SNS messages is not always related to the places where they have been created. Some studies still attempt to tie geomapping to practical purposes of urban planning. Thus Petrova et al. (2016) examine some hundred thousand posts and check-ins from different SNSs in the city of Samara in order to generate town planning recommendations.. They fnd that messages are concentrated in the city center and are differentiated by gender, type of place, and topic, while locations also differ by check-in intensity, predominant sentiment of messages and the prevailing type of visitors—either locals or tourists. The authors suggest to create more attractive places in the city periphery and also to unite the most visited and the most positively assessed places in the center by a single pedestrian pathway. This conclusion seems to be based on the visual examination of maps, as the paper describes neither analytic procedures nor any methods of posterior evaluation of the effciency of the suggested town planning strategy (for more, see Chap. 32).

An interesting result about the nature of urban civic activity is presented in Voskresenskiy et al. (2016). The authors analyze 41 restricted-access and 132 open-access VK groups run by the neighbors sharing the same apartment blocks in St. Petersburg. Based on topic modeling, restricted-access groups are found to prefer such topics as mutual help, socialization and apartment repairs, while open access groups favor city-level initiatives, contentious initiatives, including court disputes with the city administration, and, paradoxically, the maintenance of their apartment blocks and yards. This research is a rare comparison of closed and open SNS groups in an urban context, although one should keep in mind that the majority of the former (91 of 132) had denied access to the researchers.

Compared to political research, sociological research of Russian SNSs is less numerous. While political science has one of its important objects of research, namely political discourse and discussion, readily available in the form of online content, sociological focus demands more links to offine reality, which makes the overall tasks more diffcult. Additionally, sociological problems of Russia generally provoke less interest from the international research community than the country's political problems.

## 19.5 Psychology and Health Studies

#### *19.5.1 Health Studies*

Health studies, as a feld of research lying at the intersection of sociology, policy studies, psychology and medicine, is very young in Russia, and the works in E-Health are few and mostly exploratory. A series of papers has been devoted to the VK groups of acquired immune defciency syndrome (AIDS) denialists, people who deny the existence of AIDS or its relation to human immunodefciency viruses (HIV), and other AIDS-related groups. The frst work by Meylakhs et al. (2014) uses netnography (an online variant of ethnography) to examine the largest community of AIDS-denialists in VK. The authors obtain a policy-relevant result that the motives of newcomers are often far from irrational and may result from negative experience with doctors or atypical medical history. In addition, persuasive strategies of the "old" community members are described which makes the authors set a new research task—to fnd a method that would discern the core of the community from its periphery. The signifcance of this task is based on the assumption that, while core members cannot be convinced to change their views, the periphery could be re-oriented. This task is addressed in Rykov et al. (2017) with the help of SNA and regression analysis. The authors indeed fnd a correlation between some network and activity measures, on the one hand, and the core-periphery status of a user as determined by hand coding of his/her messages, on the other. However, as in (Smirnov 2018) the set of the examined predictors is not suffcient to classify the users correctly, which is why hand coding seems to be still needed.

Meylakhs' conclusions about the motivation of AIDS-denialism newcomers echo qualitative research on coping strategies of HIV-positive people (Dudina and Artamonova 2018). The authors exploit the anonymous character of the respective Russian-language forum obtaining confessions that, in the authors' opinion, would have never been possible in face-to-face interviews. On the whole, this research describes well-known stages of coping with chronic illness and the related problems, such as shock, denial, acceptance, status disclosure and stigmatization.

An attempt to describe interests of drug users based on social network data is made in Yakushev and Mityagin (2014). The authors apply a keyword-based search while crawling Russian-language LiveJournal accounts in order to fnd users who write about drugs. They also exploit an LJ feature allowing users to include tags representing their interests and perform a statistical test to fnd out which interests are typical among those users who write about drugs, as compared to those who do not. The main problem with this approach, as the authors themselves indicate, is the lack of equivalence between those who write about drugs and those who actually use them.

Thus, studying of various online communities in Russian social media is one of the research avenues in health studies, which open up great prospects for in-depth study of the structure, communication network, and leadership phenomenon in different, including hidden and hard-to-reach, populations.

#### *19.5.2 Psychology*

As mentioned earlier, psychological research based on Russian-language social media is least focused on Russia, but more often attempts to establish onlineoffine connections by seeking to predict psychological traits or conditions with social media data. Thus, Semenov et al. (2015) try to predict depression propensity with the data from VK accounts, including different network metrics, and reach area under ROC (receiver operating characteristic) curve (AUC) metric of 0.84 which is comparable to other research in the feld. The main problem of this research, similar to Yakushev and Mityagin (2014), is that the training set of users with depression propensity is compiled of those who contributed to discussion threads on being suicidal in depression- and suiciderelated VK communities. This problem may be resolved in two different ways: by either collecting ground truth on psychological conditions outside social media, as in Panicheva et al. (2016) or by using social media data not as an indicator of "true" psychological condition but as a source of users' selfrepresentations, as in Bogolyubova et al. (2018).

In the latter work, the authors compare Instagram images used by Russianspeaking and anglophone users to express psychological distress. The truthfulness of those expressions is thus left out; this lets the authors concentrate on the observable data and make interesting fndings about signifcantly more frequent use of images containing text by anglophone users. The authors connect this fnding to the lack of culture of verbal psychological self-expression in Russia. It should be noted that in this research the agreement between coders who manually assessed the images was not very high, which is a common problem for this type of studies based on human labeling.

Panicheva et al. (2016) develop a Facebook application to collect the ground-truth data about users' psychological traits—in their case, the so-called dark triad. They manage to obtain both the completed questionnaires and the text data from almost 2000 Russian-speaking users which is a huge number for psychological research. Using text data to predict the dark triad, the researchers, however, refuse from constructing a single model: as they are interested in evaluating the effect of each linguistic feature, not in the accuracy of prediction; they acknowledge the problem of distortion of signifcance levels in the models with too many predictors and apply a special correction procedure. For some reason, this problem is seldom raised outside psychological community, although it is typical for other tasks using such high-dimensional data as texts, and attention to this problem is a special value of the research by Panicheva and colleagues. At the same time, in their work, as only a limited number of user messages are available, and the sample is not described, the biases that might be introduced by these factors may be in fact more signifcant than those that the authors are struggling against.

An interesting extension of this research is presented in Bogolyubova et al. (2018) where the authors relate users' linguistic behavior, their psychological traits and the propensity to engage in harmful online behavior. They fnd out that one of the dark triad components—psychopathy—is the best predictor of such behavior. They also use a different strategy to deal with linguistic features by frst representing words as word vectors (lists of words most closely associated with each given word) and then clustering them into 182 clusters. They use these clusters as harmful behavior predictors with the same procedure of signifcance correction as in their frst paper. It should be said that, just like topic modeling (for more, see Chaps. 23, 25 and 24), both word embeddings and clustering algorithm used are unstable, and when combined can produce an indefnite number of different solutions with the same data.

A task similar to Panicheva (2016) is addressed in Rubtsova et al. (Rubtsova et al. 2018): the authors seek to fnd associations between user account features in VK and the types of teenager personality accentuations as defned by Lichko (1983). A major limitation of this research is that while Lichko's classifcation contains 11 types of personality, the authors manage to survey only 88 teenagers. This again raises the problem of big data collapse into small data due to constrained access to one type of data needed. This problem is also present in the research by Belinskaya and Bronin (2015) which is a reduced replica of the famous study by Youyou et al. (2015). Both teams use quasi-experimental design to measure the accuracy of perception of the most important personality traits—the so-called Big Five (Piedmont 2014)—by FB or VK users, respectively. For this, they ask one group of subjects (the assessed) to fll in the Big Five questionnaire, while the other group of subjects (assessors) are asked to fll in the same questionnaire on behalf of the assessed subjects. The differences between the two studies are, however, more signifcant than their similarities. First, Kosinski's team tests the accuracy of those who know the assessed people well, while Belinskaya and Bronin focus on those who have only met their friends online. Second, Kosinski and colleagues, by developing and promoting a FB application, manage to collect 86,220 observations, while the Russian authors collect only 30 offine assessments from 15 assessors. This turns the problem of big data collapse into a problem of digital divide in science: while collecting big data online seems cheap at the frst glance, this is not the case in practice. On the contrary, substantial fnancial resources and time are needed to conduct large-scale research with social media data.

## 19.6 Conclusion

In this chapter we reviewed both the works on the Russian-language social media and the Russia-related topics that can be studied with social media data in general. We have shown that Russian SNSs give very broad opportunities for research—broader than most international SNSs do. However, this potential stays somewhat underused due to a number of factors, including the lack of resources for researchers within Russia and the lack of interest to the opportunities given by the Russian SNSs from the international scholars. The sphere that generates the largest interest from the international researchers is Russian politics, and this is refected in the dominant position of this topic among Russian SNS-based studies. Sociological research is somewhat fragmented, and psychology studies are least of all related to Russia, with some strong studies done by the Russian scholars not using Russian data at all (Buraya et al. 2018).

In our review we focused both on the opportunities and problems of social media research. Our goal was to go beyond the strengths and limitations of concrete works and to highlight the common trends, especially the limitations of the feld because they are seldom spoken about in research papers, since they tend to report success rather than failures.

The opportunities include the ability to obtain large observational data collected in a non-intrusive manner and the ability to scale the research that otherwise would be bound to very small laboratory experiments or qualitative feld work. Additionally, the fact that the data of the Russian-language SNSs come mostly from the Post-Soviet space gives an opportunity to study various political, social and psychological phenomena outside the Western context where most social research data come from. Finally, social media are an important key to a society where other types of data are often less available than in more transparent countries.

The limitations are, however, also large. First, online digital traces, in order to be meaningful, often have to be combined with other types of data that are not so easy to collect and that become a bottleneck on the way to large samples. This is where we observe the effect of big data collapse. Second, SNS data have various problems of representativity in terms of their ability to represent both offine and online phenomena. Sampling network data and especially textual data is generally a poorly developed methodological area, while these types of data are the core of digital traces left by humans on social media.

Finally, methods of SNS data analysis are lagging behind the techniques available for data collection. The existing approaches are very complex, and they hide many caveats that social scientists are often unaware of. Instability of the majority of text-clustering techniques, absence of statistical inference methods for non-independent (networked) data, lack of approaches to work with power-law distributions so common for SNS data compromise the validity of many of the existing studies without social scientists being fully able to grasp the scale of the problem. Nevertheless, an open discussion of these methodological diffculties can enrich our understanding of the feld of social media research and enhance its development.

**Acknowledgments** This work is an output of a research project implemented as part of the Basic Research Program at the National Research University Higher School of Economics (HSE University).

## References

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

CHAPTER 20

## Digitizing Archives in Russia: Epistemic Sovereignty and Its Challenges in the Digital Age

*Alexey Golubev*

## 20.1 Introduction

In March 2016, the Supreme Court of the Russian Federation examined a recent decision by the Ministry of Culture, the parent body of the Federal Archival Agency (Rosarhiv), to ban personal use of cameras, smartphones, and other technical devises for copying documents in Russian archives. During court hearings, a representative of the ministry argued that free and unlimited digitization without supervision by professional archivists would likely cause increased wear and damage to historical documents. She also argued that the current ban did not violate the right of free access to archival documents and hence to historical knowledge. This position received support from many professional archivists; one of their arguments was that, if unrestricted copying of archival materials was allowed, archives would be unable to guarantee the authenticity of copies, which, in turn, would lead to manipulations of historical evidence on a large scale. Nevertheless, the Supreme Court ruled that this decision was unlawful and it had to be repealed (Galanichev 2016, 299–300; Druzin 2018, 4–5).

I am grateful to David Brandenberger, Tatyana Doorn-Moisseenko, Joan Neuberger, Serguei Oushakine, the participants of the University of Houston Digital Research Commons lecture series, and the editors and reviewers of this volume for their insightful comments and suggestions that helped me improve this chapter.

A. Golubev (\*)

University of Houston, Houston, TX, USA e-mail<EMAIL_ADDRESS>
<sup>©</sup> The Author(s) 2021 353

D. Gritsenko et al. (eds.), *The Palgrave Handbook of Digital Russia Studies*, https://doi.org/10.1007/978-3-030-42855-6\_20

Archive users did not have much time to enjoy free and unlimited copying. In April 2016, Rosarhiv was transferred from the Ministry of Culture to the Presidential Administration of Russia, signifying that its head now reported directly to Vladimir Putin. Using its new legal status, in September 2017, the agency introduced a new regulation that allowed the use of personal cameras for copying, but only by permission (that could take days or even weeks) and for a fee. This regulation was challenged in the Supreme Court as well, but this time the court ruled that Rosarhiv did not violate any law and the practice of charging archive users for making digital copies with their own devices was legal (Kurilova 2019). As a result, Rosarhiv regained full control over the digitization of archival materials, even when it is done by private users for a personal purpose.

This story highlights the extent to which Russian state agencies and offcials are concerned with digital reproducibility of historical documents as a phenomenon that challenges their control over the production of historical knowledge. According to the code and practice of Russian law, access to historical documents is a civil right, and while this right is routinely violated by state institutions, in many cases it has been successfully enforced through legal battles. At the same time, digitization of historical documents turned out to be a more controversial issue. The relative ease of the digital access and reproduction implies that online archives of historical documents can be not only produced at a low cost but also be available to a much bigger audience than before (for an example of such archives, see Chap. 21). This offers new opportunities in terms of communication of knowledge, but it also means that the circulation and production of historical knowledge becomes less centralized as it moves away from the expert-controlled domains such as edited volumes published by academic presses into a more egalitarian information society that trespasses national borders and jurisdictions where digital archives can be curated by virtually anyone. Given how important the maintenance of a coherent national narrative is for many Russian top offcials (Brandenberger 2015, 200–205; Shteynman 2016, 107–108), it is unsurprising that Rosarhiv is very cautious when it comes to releasing the documents from its collections on the World Wide Web.

Yet the politics of history represent only one aspect of the current situation with digital archives in Russia. The unwillingness of Russian archives to outsource digitization of their materials means that when they start their own digitization projects, as a rule, they end up with high-cost solutions. An August 2018 post published by the Archival Committee of St. Petersburg in its Facebook group claimed that it took the archives ffteen years to digitize the parish register books of St. Petersburg; the same post claimed that a complete digitization of all collections of the St. Petersburg archives would require at least 45 billion rubles (ca. \$650 million at the current exchange rate) worth of funding and presumably decades of work (Archival Committee of St. Petersburg 2018). As a result, managers of Russian archives have to choose strategically which documents and collections should be presented online. Since most of the archives are chronically underfunded, they also actively solicit external funding both domestically and internationally in order to push forward their digitization efforts and get a better public outreach. The research and political agenda of funding agencies thus becomes part of the archival digitization process in Russia.

This chapter examines the production of digital archives in a broader context of the political economy of historical knowledge in Russia. The resolution of Rosarhiv to control which and how many documents its users copy digitally should be treated as a symptom signaling the epistemic anxieties of the state authorities. The archive, as the works of Michel Foucault, Jacques Derrida, Ann Stoler and many others have shown, is a key institution of the state power over history: it defnes the dominant forms of knowledge, its limits and silences, establishes hierarchies of voices from the past, and produces experts with authority to interpret its documents. In other words, the archive is a powerful tool that transforms the totality of the historical experience preserved by a certain community or society into a structured hegemonic form that privileges some parts of this experience and silences other (Foucault 1977, 155–164; Foucault 2002, 146–148; Derrida 1996, 3–5, 10–13, 19–20; Stoler 2006, 44–51). However, modern information and communication technologies represent a formidable challenge to maintaining this epistemic sovereignty as they simplifed to the extreme a precise reproduction of historical documents and production of digital archives, thus diluting the state's sovereign control over historical knowledge. The situation is further complicated by a relatively marginal place of Russian archives in the global economy of knowledge where the demand for the digitization of their materials often comes from outside of the Russian national borders and represents political and cultural interests of nonstate agents. As a result, a study of digital archives in Russia provides a unique perspective on the ways in which the Russian state adapts to the digital age.

This chapter starts with a discussion of the early digitization efforts during the 1990s and early 2000s that were largely funded by international funding agencies, most prominently the Open Society Institute, whose activity is presently banned in Russia. It then examines the growing concern of the state authorities over the reproduction of historical documents online and their efforts to control the production of digital archives through specialized funding agencies (such as the Russian Foundation for Humanities that in 2016 merged with the Russian Science Foundation) and restrictive measures. In the concluding section of the chapter I discuss the current state of digital archives in Russia, which is not limited to the activities of federal and international agencies, but also involves a great deal of private initiative. Yet despite the multitude of actors and large-scale digitization efforts, I argue, Russian digital archives are curated to conform to the dominant paradigms of historical knowledge and have so far failed to induce an epistemological shift in the studies of Russian history.

## 20.2 Archival Revolution: International Actors and Early Digitization Efforts

The early effort to digitize historical documents from the former Soviet archives was an integral part of the archival revolution that started at the turn of the 1990s following the perestroika and led to an unprecedented openness of Russian archival collections for both the scholarly community and general public (Raleigh 2002). In Russia, this effort was spearheaded by international organizations. Between 1992 and 1996, for example, the Hoover Institution on War, Revolution, and Peace with the UK-based company Chadwyck-Healey Ltd microflmed approximately 14,500,000 pages of historical documents and inventory lists from the central Russian archives (Davies 1997, 101–102). In the mid-1990s, the Yale University Press launched the Annals of Communism book series with English translations of thousands of formerly classifed documents of the Communist Party and the Soviet government. Another archival collection that attracted signifcant international interest in the early 1990s was the documents of the Third (Communist) International, or Comintern, stored in RGASPI (*Rossijskij gosudarstvennyj arhiv social'nopolitičeskoj istorii*, Russian State Archive of Social and Political History). Since the Comintern as an instrument of Soviet infuence coordinated activities of Communist parties and affliated groups in numerous countries between 1919 and 1943, its records amount to 20 million pages written in multiple languages. The enormous size of these archive collections and imperfect inventory lists made their analysis complicated, as even a preliminary research required long-term trips to Moscow.

In 1992, the Council of Europe, the International Council of Archives and Rosarhiv initiated a discussion of a large-scale project that involved leading scholars on the history of the Comintern. The discussion aimed to prepare a large-scale project to create a database describing the entire Comintern collection at RGASPI (over 200,000 documents) and to digitize the key documents from the collection (ca. one million pages out of the total number of 20 million). In June 1996, the International Council of Archives and Rosarhiv signed a framework agreement that established the International Committee for the Computerization of the Comintern Archives (INCOMKA) under the auspices of the Council of Europe. The funding for this large-scale digitization project came from numerous sponsors, including many European archives, the Library of Congress, and the Open Society Archives. By 2003, the project was completed including 1,059,354 digital images of archival documents (ca. 5% of the entire collection) and a searchable database of the entire collection with 239,602 entries (Doorn-Moisseenko 2005; Bachman 2005; Amiantov 2011).

Since the project was initiated at the dawn of the Internet era, the digital archive was initially hosted at the RGASPI without remote access, and its copies were distributed on CDs to the international project participants. Users had to be physically present at the RGASPI (a dedicated space was equipped with 17 workstations for this purpose) or in one of the partner institutions in order to work with the archive. However, by the time of the project completion in 2003, this principle was already outdated, and the following year a joint venture company was formed by the Dutch academic publisher, IDC Publishers (purchased by Brill in 2006) and Russian corporation ELAR to provide paid online access to the dataset. This service was hosted at www.comintern-online. com and charged between 2000 and 7500 euro for an annual subscription depending on the buyer, with revenues shared between Rosarhiv, ELAR and IDC Publishers/Brill. The archive remained behind the paywall for the next ten years, until 2013, when it was published online as part of a new initiative *The Documents of the Soviet Era* of Rosarhiv that I will discuss later in this chapter.

The digital archive of the Comintern documents is a good example, illustrating the early stage of the digitization of Russian archives. The perestroika and the frst post-Soviet decade in Russia were characterized by the state's temporary disinvestment in historical knowledge, and many national and international non-government agents sought to fll this gap proposing new epistemological models, producing new historical narratives, and publishing formerly classifed documents, at frst as books and then, as new information and communication technologies became increasingly widespread, as digital archives. The Open Society Institute (OSI)—a parent organization of the Open Society Archives which was one of the partner institutions of the INCOMKA project was the most visible actor in this sphere. Between 1996 and 2000, it granted a total of \$1,500,000 United States Dollars (USD) for different projects in the archival sphere, including the frst website of Rosarhiv (Okhotin 2001). Before the Russian authorities forced the OSI to quit its activities in Russia, it supported such projects as online databases of the archival collections of the Russian State Documentary Film and Photo Archive (Bajgarova et al. 2000), Gorbachev Foundation (Kolesov 2002), National Archive of the Republic of Kareliâ (Kadymova and Kolesova 2003), and Perm′ State Archive (Perm State Archive 2015). It was also one of the key sponsors of the society *Memorial*, a key non-government institution that publicizes knowledge about historical and contemporary state violence in Russia, that produced a database of the victims and later perpetrators of Soviet political repressions and several archives related to Soviet state violence, dissident movement, German forced labor, and oral history.

These projects had a clearly defned political agenda to educate audiences in Russia and abroad about the history of state violence, which was shared by many other international foundations that funded the digitization of archival documents in the post-Soviet countries.1 The goal to ensure a broad public outreach for these digital archives meant that they were produced as free products. A similar political agenda drove German research foundations to actively support the production of digital archives related to Soviet citizens' experience of Nazi violence during the Second World War. One of the latest projects of this kind is a digital archive of oral history interviews of former Soviet prisonersof-war and forced laborers *Ta storona* (Another Side) at tastorona.su. The archive is based on a collection of interviews of the society *Memorial*, and was funded by the German Foundation Remembrance, Responsibility and Future and the Henrich Böll Foundation, as well as OSI. Currently it provides access to 167 interviews using specially designed software that optimized the presentation of interview transcripts, their commentary, audiovisual and geospatial data, and meta descriptions (Beilinson 2015).

## 20.3 Russian Archives and Commercial Content Providers

The early stage of digitization of archival collections in Russia was also characterized by another trend: the commercialization of scholarly content. Histories of state violence in Russia were a particularly attractive subject for commercial publishers, but the trend was much bigger and included many other felds. The opening of Russian archives coupled with a huge economic gap between Russia and the First World nations during the 1990s created a situation when Western publishers were able to sign lucrative digitization agreements with Russian archives and libraries that granted them exclusive rights to distribute the resulting digital collections and archives worldwide. As a rule, Western partners provided equipment and funding for digitization, and Russian partners received digital copies of their collections that they could provide to users within their computer networks (although sometimes they retained the domestic distribution rights) as well as a percentage of sales.

The Dutch company IDC Publishers mentioned above in the context of the international distribution of the Comintern Digital Archive was one of the earliest and most active players in the digitization market of Russian historical documents and publications. It started producing Russia-related collections of primary sources for commercial distribution on microfche long before the collapse of the Union of Soviet Socialist Republics (USSR) using books and periodicals from the Slavonic Library of the National Library of Finland. As early as in 1987, it signed contracts with the Russian National Library getting a priority access to its collection of periodicals, rare books, and historical documents (Russian National Library 2004, 17). Over the next twenty years, the IDC Publishers signed similar contracts with the Library of the Russian Academy of Sciences, K.D. Ushinsky State Scientifc Pedagogical Library, Russian State Archive of Literature and Art, Russian State Military Archive, Moscow State University Library, and Russian State Archive of Social and Political History. Its team used the materials from these institutions to produce digital archives of the Artek Pioneer Camp (1944–1967), early Soviet cinema (1923–1935), Russian military intelligence on Asia (1651–1917), Jewish Theater under Stalinism, as well as extensive digital collections of Russian and Soviet periodicals. The company was remarkable for its careful market analysis, which, prior to its merger with Brill, allowed it to become a large and successful commercial content provider in the feld of Russian studies, including in digital archives. However, following its merge with Brill in 2006, Russia- and Eastern Europe-related content lost its priority for the new company management. Access to the materials digitized earlier by the IDC Publishers is still sold through Brill either as an institutional subscription or as limited-term access for individual users (Doorn-Moisseenko 2019).

A similar model was used by the Yale University Press (YUP) in a collaboration agreement with the Russian State Archive for Social and Political History to digitize Joseph Stalin's personal archive (*Fond 558*). The project was initiated in the late 2000s with the fnancial support of \$1,300,000 from the Mellon Foundation (Mellon Foundation 2007), and in 2011 YUP launched the frst version of the Stalin Digital Archive at www.stalindigitalarchive.com that over time grew to include 400,000 pages of over 28,000 documents including Stalin's personal papers, his domestic and international correspondence, and books with his marginalia. Access to the digital archive was provided through institutional subscription only. Rosarhiv as the parent organization of the RGASPI, however, retained the domestic distribution rights for the digitized copy of Stalin's archive, and launched its free version for Russia-based users in 2013 as part of the portal *Documents of the Soviet Era* at sovdoc.rusarchives.ru that I will discuss in the next section of the chapter.

Another example of a successful commercialization of digital archives of Russian historical documents and publications is represented by the East View Information Services, a Minnesota-based company founded in 1989 as the East View Publications, Inc. to distribute Soviet military journals for international audiences. Over the following three decades, it established itself as a major provider of digital content from Russia and other post-Soviet states as well as China, Afghanistan, Iran, and several African nations. Yet while for the latter regions its content is focused on exclusively contemporary affairs, its experience and expertise in the international distribution of Russian-language publications (one of its co-founders, Vladimir G. Frangulov, is a former research fellow at the Institute of World Economy and International Relations of the Russian Academy of Sciences) helped them diversify their business model by digitizing archives of Imperial-era, Soviet and post-Soviet periodicals and offering them as part of the subscription to their catalogue. The catalogue now includes digital archives of the key Soviet newspapers and magazines with a full-text search, which makes it particularly appealing for scholars (Lee and Frangulov 2014).

The fact that the archival revolution in Russia coincided with its transition to market economy and a subsequent crisis in the funding of state archives, on the one hand, and an astonishingly fast development of the new digitization technologies, on the other hand, opened a window of opportunity for Russian and Western non-governmental agents and for-proft companies to launch large-scale digital archive projects. In a way, they can be described as quasicolonial projects: exploiting economic inequality between Russian and the First World countries, they treated the Russian historical experience represented in these newly built digital archives as a commodity to be sold to the First World audiences (East View or Brill), or as a deviant experience, a lesson of what future generations had to avoid at all costs (the digital archives of the Comintern or Joseph Stalin). Yury Afanasyev, a professional historian who became an infuential politician during the late-Soviet and early post-Soviet periods, characterized the unequal relationship between Russian archives and Western content providers in precisely these terms when he interpreted the aforementioned 1992 agreement between the Hoover Institution, Chadwyck-Healey Ltd, and Russian archives as a "typically colonial exercise" (Afanas'ev 1992). It is hardly surprising that, once the Russian state agencies were able to fund their own digitization projects, their political agenda became radically different.

## 20.4 Russian Foundation for Humanities: Patching the Archival Fabric

Throughout the 1990s and into the early 2000s, domestic funding of archival digitizing activities in Russia had signifcantly lagged behind the projects supported by Western funding. It was only in 1994 that the Russian government established a specialized funding agency for social sciences and humanities, the Russian Foundation for Humanities (RFH), which had supported projects in digital humanities since 1995 (Semenov 1997, 118–119). However, limited funds and high costs of digitization activities kept them relatively small-scale: in 2015, an average one-year grant in digital humanities was 500,000 rubles, or less than \$10,000 USD in that year's exchange rates (Blinov 2012, 235). Nevertheless, the Russian Academy of Sciences and universities have actively used this funding source to digitize and make available their archival collections, and a large number of small digital archives have appeared since the late 1990s. A typical project was, for example, a digital archive of ethnographic feld records, a personal archive of a famous cultural fgure or scholar, a collection of folklore texts and performances, or a digital archive of historical periodical. The number of documents in these archives typically numbered in hundreds, sometimes thousands, although the Russian Foundation for Humanities also supported multi-year projects that resulted in bigger digital archives. A full list of digital archives produced, thanks to the funding of the RFH, currently numbers in over a hundred, so below I will only focus on a few cases to illustrate the goals, scope, and implementation of such projects.

One of the early digital archives produced with the funding from the RFH was an online collection of audio records and transcripts of folklore performances of the Karelian Research Center (KRC) of the Russian Academy of Sciences. With the earliest records dating back to the 1930s, the collection represents critical knowledge of traditional music and performances among the ethnic groups of Northwest Russia, including Russians, Karelians, Vepsians, Finns, Izhorians, and Sami. In 1999, the KRC received funding to produce an online catalogue and to digitize sample records from both the Open Society Institute and the Russian Foundation for Humanities. An early version of the archive went online in early 2000 at phonogr.krc.karelia.ru; however, the number of actual records available online was just fourteen (Vdovicyn et al. 2000, 32–34). In 2008, the KRC received another grant from the RFH to make available transcripts of folklore texts recorded or written down by Soviet ethnographers, which resulted in the publication of over 400 original texts at folk. krc.karelia.ru. In 2012, yet another grant from the RFH allowed the center to add 70 audio records and their transcripts to the digital archive at phonogr.krc. karelia.ru/folklor. This amount represents a fraction of the records stored in the archive of the KRC, yet it provides valuable material for those scholars of the region and members of the general public who are interested in its traditional cultures. Similar projects have been implemented elsewhere in Russia, such as a digital archive of the folklore of the peoples of Siberia developed by the Siberian Branch of the Russian Academy of Sciences since 2014 folk.philology.nsc.ru, or a digital archive of ethnographic records from the Kaluga region of the Moscow Tchaikovsky Conservatory produced from a grant of the RFH in 2007 at folk.rusign.com.

The RFH also supported projects that sought to produce digital archives from fragmented collections, often in separate geographic locations, thus providing scholars and the general public with a single point of access to a certain periodical or a personal collection. The author of this chapter was a leading team member in one of such projects to create a digital archive of the surviving issues of the Russian imperial newspaper *Oloneckie gubernskie vedomosti* (OGV, or News of the Olonec Governorate). OGV was an offcial newspaper of the Olonec Governorate from 1838 to 1917; apart from offcial news and government decisions, it also published materials on history, economy, ethnography, and culture of Northwest Russia. By the mid-2000s, several libraries and archives in Petrozavodsk and St. Petersburg had partial collections of the newspaper, but in order to protect the fragile newspapers, most of them signifcantly restricted access to their collections (for example, the only categories of users who could work with the collection of the OGV issues from the library of the Karelian Research Center of the Russian Academy of Sciences were scholars with advanced degrees and graduate students). A digital archive of the newspaper simultaneously solved both problems by providing a consolidated collection of the surviving issues in free access. Given the complex logistics and a large scale of work, the RFH supported a three-year long project (2006–2008). It was implemented by a team from the Petrozavodsk State University, which digitized OGV issues from the National Archive of the Republic of Karelia, National Library of the Republic of Karelia, Academic Library of the Karelian Research Center, and Russian National Library in St. Petersburg. The result was a digital archive of initially 4670 issues of the newspaper (Golubev and Fotina 2007). After the completion of the project, it was maintained by the National Library of the Republic of Karelia that was able to digitize an additional 400 issues; as of now, the archive provides free access to 5064 issues at ogv.karelia.ru. Similar projects supported by the RFH include, among others, a digital archive of Ivan Bunin's personal papers at bunin-rgali.ru that consolidated the holdings of the Russian State Archive of Literature and Leeds Russian Archive Collections, and a digital archive of ethnographic records of feld trips of the Moscow State University and St. Petersburg State University at ethnoarchive.spbu.ru. Apart from the Russian Foundation for Humanities and, since 2016, the Russian Science Foundation, similar small-scale digitization projects were supported by several federal and regional programs run by the Russian Ministry of Education and Russian Academy of Sciences.

## 20.5 The Return of the State

This system of grants run by the RFH helped to bring online many small archives of Russian universities and institutes of the Academy of Sciences, but at the same time it had a priori too limited a scope to engage in a large-scale digitization of archival collections of the central and regional Russian archives. The latter work became possible due to a particular conjunction of state and business interests in Russia. In 2002, the Russian government launched a federal program called *Èlektronnaâ Rossiâ* (Electronic Russia) with the goal to accelerate the use of new information and communication technologies in state administration. The program was designed for the period of 2002–2010, and while it failed to achieve the original goal to create a comprehensive online access to state services, one of its by-products was the appearance of a new segment in the Russian Information Technologies (IT) market, namely, a stable demand for commercial solutions in the sphere of e-governance. Among the companies that benefted from the new market conditions was Electronic Archive Corp. (ELAR). Established in 1992, it specialized in developing and providing of highly automated digitization technologies, and after 2002 it became the leading contractor of Russian government agencies, including Rosarhiv, in such areas as digitization of archives, development of digitization hardware and software, and digital archive management systems (Plotnikov 2014). Unlike Western commercial publishers and content providers such as Brill and EastView, ELAR uses a different business model: namely, state contracts to produce digital archives. In this model, Rosarhiv has a full authority over the selection of the content, and ELAR as the contractor does not acquire any distribution rights for the digitized content, which is published in open access. Since its profts come exclusively from the amount of completed work, its management is interested in lobbying more projects with the Russian government and its agencies, which has become an important driving force in the digitization of Russian archives.

The digital archives produced, at least partially, within this model include Rosarhiv's *Documents of the Soviet Era* and *The People's Memory* contracted by the Russian Ministry of Defense. *Documents of the Soviet Era* was launched in 2013 at sovdoc.rusarchives.ru and from the very beginning comprised several earlier document collections, namely, the aforementioned digital archives of the Comintern and of Joseph Stalin. According to the agreement with the Yale University Press, the website restricts access to Stalin's archive from non-Russian and non-Belorussian Internet protocol (IP) addresses. At the same time, several document collections were digitized exclusively for this project, including 30,000 electronic copies of documents of the *Politbûro* for 1919–1932 (May 2013), 240,000 electronic copies of documents of the Soviet State Defense Committee (June 2015), 122,000 copies of documents about the Russian Revolution of 1917 (December 2017), and several smaller collections. In his interviews, the current head of Rosarhiv Andrej Artizov repeatedly emphasized that the purpose of the digital archive was to educate national audiences about the complexity of the Soviet period of Russian history (Artizov 2018). In doing so, the management of Rosarhiv—which in these contexts represents the historical profession as such—asserts its authority in the production of knowledge about Russian history, thanks to the seemingly comprehensive nature of their digital archive as well as vast possibilities to enlarge it by digitizing additional materials when necessary. Rosarhiv has used this positionality in order to advance the state's agenda in such questions as the legitimacy of Russia's annexation of Crimea, the treat of Ukrainian nationalism, and the complacency of Britain and France in the rise of Nazism in Europe, with the publication of digital copies of historical documents serving as a technique to challenge the widespread accusations of illegitimacy of Russia's claims for Crimea, the Ukrainian claims that the Holodomor was an intentional act of genocide against the Ukrainians, and of the critical role of the Molotov-Ribbentrop Pact in provoking the outbreak of the Second World War (Artizov 2014, 7–10; Brandenberger 2015, 202–203).

The management of Rosarhiv places a special emphasis on its comprehensive approach to the digital publication of archival documents: instead of handpicking sources to highlight certain aspects of the Soviet historical experience, Rosarhiv chose to make available entire document collections. In the logic of their creators, this approach should produce a more credible picture of the historical past than the partial digital archives of Vladimir Bukovskij (bukovskyarchives.net), Aleksandr Yakovlev (www.alexanderyakovlev.org), and Dmitrij Volkogonov's collection in the Library of Congress (National Security Archive 2017). Their authors, who at one or another point in the late 1980s and 1990s acquired access to classifed collections of Russian archives, understandably focused on more sensational and controversial documents (Bukovskij 1996, 51–63). Yet, while providing authentic copies of important historical documents, these digital collections fail to present the totality of Soviet decisionmaking at the top level that the *Documents of the Soviet Era* can claim.

Needless to say, this claim of totality and objectivity disguises the epistemic and political foundations of the actual archival collections in the possession of Rosarhiv (Rosenberg 2001, 82–84). Moreover, while its management and staff are concerned with the questions of epistemological sovereignty, their understanding of how to "decolonize" Russian history is framed primarily in terms of data management with archives performing the function of a mediator, but also a censor, between historical documents and professional historians. This logic is based on the understanding of historical documents deposited in archives as the most authentic and epistemologically reliable evidence about the Russian past, which is why, for example, Artizov argues that the production of digital archives such as the *Documents of the Soviet Era* is the best strategy to refute "false" interpretations of Russian history (Artizov 2014, 7). What is missing in this understanding is that the documents themselves do not provide new knowledge, but instead replicate the same interpretive categories that were laid in the foundation of original archival collections with their explicit and hidden hierarchies, silences, gaps, and exclusions.

The corporation ELAR played a key role in the development of another digital archive called *The People's Memory* at pamyat-naroda.ru that combines archival data and copies of original documents related to Soviet servicemen during the Second World War. The archive is based on the collections stored in the Central Archive of the Russian Ministry of Defense, and currently includes digital copies of 425,000 original documents. Its structure is much more complex than that of the *Documents of the Soviet Era*: in addition to presenting electronic copies of historical documents, the developers of the archive extract biographical data from them and combine personal information from various sources into coherent biographies. The archive also provides access to ca. 100,000 digitized military maps to trace the movements of Soviet detachments and servicemen during the war, and a rich collection of original battle reports. Currently, the development team collaborates with German archives to add to *The People's Memory* information about Soviet prisoners-of-war. The offcially postulated goal of this archive is, like in the case of the *Documents of the Soviet Era*, to build up a critical mass of documentary evidence so that an unbiased and objective understanding of the Soviet Union's participation in the Second World War would appear as a result of free access to these documents. At the same time, apart from epistemic concerns, this project also has an important humanitarian mission: to help the relatives of the Soviet servicemen to fnd relevant biographic information about their lives and deaths.

## 20.6 Vernacular Archives

In recent years, thanks to the ongoing digital revolution that makes digitization technologies increasingly cheap and easy to use, this discrepancy was addressed when a new phenomenon appeared that can be characterized as vernacular digital archives: namely, projects created, maintained, and supported by volunteers who are driven by a desire to preserve those aspects of the Russian historical experience that have been neglected due to a lack of funding or interest by the state archives. Two prominent projects include a digital archive of Soviet-era radiobroadcasts *Audiopedia* at audiopedia.su and a digital archive of diaries *Prozhito* at prozhito.org (for more, see Chap. 21). *Audiopedia* grew from an earlier project *Staroe Radio* (Old Radio, staroeradio. ru), when in 2007 Yury Metelkin, a former Soviet rock-musician, launched an online radio station that broadcast Soviet-era programs, including audiobooks, audio-plays, science broadcasts, and so on. Over the following years, the archive of *Staroe Radio* grew through the efforts of volunteers who digitized their old records and donated them to Metelkin; in 2018, it acquired an entire archive of the Irkutsk radio station that includes federal and local records from the 1940s on, or ca. 80,000 phonograms. *Prozhito* is a later project that dates back to 2015 when its founder, Mikhail Melnichenko, decided to produce a historical corpus of texts that could be used to trace the use of certain concepts. The project employs a large group of volunteers to identify, scan, process, and upload diary entries (Nordvik 2018, 43–44); as of early 2019, it provides access to nearly 3000 diaries, mainly from the Soviet era.

Both *Audiopedia* and *Prozhito* are non-commercial and non-government projects, and as such they show a large potential of public and digital history in terms of preserving and communicating historical evidence. Yet both ultimately work within the same paradigm of history as a national project that the *Documents of the Soviet Era* and *The People's Memory* are part of. Metelkin explicated this logic in his explanation of why he decided to preserve, digitize, and make available old radio broadcasts, mentioning the "preservation of the [national] language, education, cultural traditions, and ultimately national selfidentity"—or everything that is traditionally identifed as functions of state power—as the driving factors of his project. The very fact that both projects inadvertently prioritize the experience of the Soviet educated class, that is, the people who are more likely to internalize and embody the national agenda, means that the digital technologies do not challenge the logic of the national archive but rather ensure a better and more effective communication of knowledge produced through it to national audiences.

## 20.7 Conclusion

The examples discussed above show that the Russian state has sought to use digital archives to frmly re-establish itself through its institutions (primarily Rosarhiv) as the main authority in the production of knowledge of Russian history, especially during the Soviet period, which remains extremely contested. Symptomatically, other post-Soviet states have used similar strategies: for example, Latvia whose government has persistently interpreted the period between 1940 and 1991 as an experience of double (Soviet and Nazi) occupation has recently made accessible documents of the Latvian offce of the KGB (*Komitet gosudarstvennoj bezopasnosti*, Committee for State Security) at kgb. arhivi.lv with the names of its agents. The online publication of these documents by the State Archives of Latvia follows the same logic as the development of digital archives in Russia. The digitization of historical documents remains an expensive business that the state agencies and non-governmental organizations (NGO) use strategically to create an online presence of document collections that, from their perspective, beneft the common good, the understanding of which can vary dramatically from the national interests to global human rights to objective knowledge.

The archival revolution of the early 1990s and the fact that it was used by a number of international actors (Library of Congress, Hoover Institution, IDC Publishers, etc.) to reproduce valuable collections of historical sources put Russian government bodies such as Rosarhiv and the Ministry of Defense in a situation where, despite their full control of the most important archival collections from Russian and Soviet history, they had to take proactive steps to act as the authoritative sources of critical evidence about Russian history. They responded to this challenge with ambitious digitization programs that provided an unprecedented level of access to primary sources in Russian history. At the same time, the political and epistemic concerns that drove the production of these archives forced their patrons and developers to concentrate on a very narrow list of topics that is limited to political and military history. Grants for digital projects provided by the RFH addressed a broader number of themes in social, cultural, and intellectual history, but in a very fragmentary manner due to limited funding.

The digital reproduction of historical documents and their communication online thus performs largely the same functions as the traditional archive, namely, maintaining state sovereignty over history, reinforcing silences in dominant historical narratives, and endowing certain groups of experts with the authority to defne the authenticity and validity of selected facts and sources. Even though such a phenomenon as the vernacular archive has become increasingly prominent in recent years, it has yet to challenge this situation, since the developers of these digital archives have so far followed the preexisting structures and hierarchies of knowledge that prioritize the historical experience of privileged political and social groups.

## Note

1. For example, during 2006–2007, the author was an investigator of the project *Missing in Karelia: Canadian Victims of Stalin's Purges* funded by the Canadian Social Sciences and Humanities Research Council (principle investigator Prof. Varpu Lindström of York University). The project resulted in a database of Finnish-Canadian and Finnish-American immigrants to the Soviet Union that compiled information from several thousand of archival documents from the National Archive of the Republic of Karelia (http://missinginkarelia.ca/, accessed December 13, 2013); after the domain name expired in December 2013, the digital archive was deposited by the National Archives of Finland and the National Archive of the Republic of Karelia (currently unavailable online).

## References

the Soviet Era. History and the Present. To the 90-Year Anniversary of the Russian State Archive of Socio-Political History]. *Vestnik arhivista* 1: 192–198.

———. 2018. Â blagodaren arhivistam za ih samootveržennyj trud [I Am Grateful to Archivists for Their Selfess Work]. *Otečestvennye arhivy* 1: 3–6.

Davies, R.W. 1997. *Soviet History in the Yeltsin Era*. London: Palgrave Macmillan.

Vdovicyn, V.T., V.P. Kuznecova, A.A. Bedorev, N.B. Lugovaja, S.M. Rusakov, and A.D. Sorokin. 2000. Sozdanie èlektronnoj versii arhiva fol'klornoj fonoteki IÂLI KarNC RAN [Development of the Digital Archive of the Folklore Phonogram Collection of the Institute of Language, Literature and History of the Karelian Research Center of the Russian Academy of Sciences]. *Vtoraâ Vserossijskaâ naučnaâ konferenciâ "Èlektronnye biblioteki: perspektivnye metody i tehnologii, èlektronnye kollekcii,"* 32–38. Conference Proceedings, Protvino, September 26–28.

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

## Affordances of Digital Archives: The Case of the *Prozhito* Archive of Personal Diaries

## *Ekaterina Kalinina*

## 21.1 Introduction

Despite being the guardians of public records Russian archives not always grant the right of public accessibility (TASS 2018; Rambler 2017; Komissiâ 2016; Slobodenyuk 2019). Not being able to get access to archival materials, professional historians and amateurs alike have to look for alternative ways of getting hold of historical sources, and in such a situation digital databases can become their salvation (Venyavkin 2017).

Today, one can get access to a wide range of historical documents online: project *Ustnaâ istoriâ* (Oral history) makes recorded talks with famous intellectuals accessible through a web platform (http://oralhistory.ru); project *Prozhito* digitizes and publishes personal diaries (http://prozhito.org); database *Otkrytyj spisok* (Open list) makes it possible to fnd information about persons who fell victim to the Soviet repression machine (http://ru.openlist. wiki); photo databases such as *Pastvu* (http://pastvu.com) and *Istoriâ Rossii v fotografâh* (History of Russia in photographs, http://russianphoto.ru) grant access to a wide range of photo materials.

These and other similar initiatives carry a promise of wider access to historical sources. Scholars even stress that digital archives form "public alternatives to offcial constructions of the past and ways in which that past is to be studied" (Lapina-Kratasyuk and Rubleva 2018, 164; Garde-Hansen et al. 2009). Alexandra Herlitz and Jonathan Westin (2018, 451) believe that "[c]onfating

E. Kalinina (\*)

Jönköping University, Jönköping, Sweden e-mail<EMAIL_ADDRESS>
<sup>©</sup> The Author(s) 2021 371

D. Gritsenko et al. (eds.), *The Palgrave Handbook of Digital Russia Studies*, https://doi.org/10.1007/978-3-030-42855-6\_21

different archives digitally makes the archival substance less vulnerable to any agenda of an archiving individual and may therefore lead to a greater objectivity and reliability of the accumulated material." In Russia such digital platforms become essential players in political, social and cultural life by allowing people to learn about the past from other sources rather than those that are state approved. This means that digital archives have the potential to not only challenge established historical discourses but also question the leading role of the state in the production of historical narratives.

This idea about the democratizing potential of digital archives is rooted in the belief that digital technologies are the solution to many problems. Recent studies of digital media, however, show that scholars should be more careful when stressing the democratic potential of the web, as internet is not necessarily democracy's magical solution (Fuchs 2017; Morozov 2011; Nisbet et al. 2012; Rød and Weidmann 2015; Stoycheff et al. 2016). When archival collections become digital, various legal constraints and the fragmentary nature of archival records might lead to the reproduction of already existing biases. So, while some scholars (Herlitz and Westin 2018) see digital archiving as a possibility to safeguard and disseminate data to wider publics, others (Aghostino 2016; Azoulay 2012) insist on a more critical approach to digital archives by arguing that the non-neutral and ideological nature of digital infrastructures predetermines what type of content becomes visible and how much visibility it gets. Hence, in order to study the potential of digital archives for the democratization of history, one should look at what users can and cannot do in order to create new narratives that can disrupt dominant discourses of power.

Therefore, the aim of this chapter is to study affordances of digital archives, that is, the properties that allow users to perform certain actions on the platforms, in order to explore their democratic potential. To be able to do that, affordance analysis, which allows one to investigate the technological and organizational structures of digital platforms, the amount and quality of data available, the social underpinnings entangled in technologies and the degree of user participation, is applied to the Russian digital archive of diaries *Prozhito*.

The research questions that guide this chapter are: what kind of data is (not) available in the archive and why? What information about affordances is available and what does it tell us about the composition, constraints, limitations and affordances of the archive? How much participation does the archive allow? What kind of participation does the archive support? These questions are addressed by focusing on *Prozhito* as an environment that allows certain actions and forms of participation, rather than on specifc uses of *Prozhito*. This means that this study is not a reception study but rather a research of digital archives as media environments.

In order to address the above-mentioned scholarly interest, the chapter starts with a section outlining the theoretical framework and methodological guidelines, followed by the analysis of *Prozhito* and a brief conclusion summarizing major fndings.

## 21.2 Theoretical Tools for Unpacking Archives

Some scholars believe that archives play an important role in the formation of national consciousness and in the development of democratic liberal citizenship, because they preserve evidence which is paramount for the work of justice and crucial for keeping individuals, groups and institutions accountable (Joyce 1999). Jacques Derrida, for example, claims the centrality of the archive to the existence of democratic society by stating that "[e]ffective democratization can always be measured by this essential criterion: the participation in and access to the archive, its constitution, and its interpretation" (Derrida 1995, 4).

Scholars also point out that archives are hardly neutral collections of records but rather environments where both technical and organizational structures produce as much as record events (Derrida 1995, 17) and organize data in a way that might "lead later investigators in a particular direction" (Manoff 2004, 16). Gillian Rose (2012, 228) argues that archives "have effects on what is stored within them" and on "those who use them." Jaimie Baron (2014, 109ff) calls this process *archive effect* and explains it as a human response toward archival material, which can be triggered by the engagement of a person with archival documents and even purposefully employed to activate the public.

As archives are environments with specifc technological and organizational structures the users come in contact with, the concept of affordances could be applied in order to study archival properties and what users can and cannot do with them.

The term "affordance" was frst coined by psychologist James J. Gibson in his seminal book *The Ecological Approach to Visual Perception* (1979) to describe the properties of the environment. Gibson explains affordances as interconnected action possibilities offered by the environment to the subject. He says: "an affordance is not bestowed upon an object by a need of an observer and his act of perceiving it. The object offers what it does because of what it is" (Gibson 1979, 139). In other words, an affordance is the possibility of an action available in the environment that is independent of the subject's ability to perceive this possibility. At the same time an affordance exists relative to action capabilities of the subject. This means that an affordance of an environment might exist, but it only can be activated if the subject has the capacity for an action.

At the same time what a subject perceives about affordances depends much on the information he/she has about them. Depending on the presence or absence of affordances, and the presence and absence of information about them, one can divide affordances into the following types (Gaver 1991): *perceptible* affordances (both information and action exist), *false* affordances (information about the affordance might exist but the affordance itself is absent*)*, *hidden* affordances (affordance exists but information is hidden), and *correct rejection* (absence of information and affordance) (Gaver 1991).

Gibson (1979) also suggests two types of affordances: *positive* and *negative*, where positive affordances stand for properties that allow certain actions and negative affordances for properties that do not allow certain actions. They can also be called *platform constraints*. In this text the term "platform constraints" rather than "negative affordances" will be used. Constraints will be divided into technological, legal and ethical constraints in order to cover the whole spectrum of systematic issues.

One has to keep in mind that environments can be characterized by multiple affordances that exist in relation to each other. The notion of *nesting* helps to conceptualize these relationships between different affordances of environments by suggesting some sort of hierarchy between them. Turner (2005) suggests dividing affordances into *simple* affordances, that is, usabilities of the environment or objects, and *complex* affordances, that is, properties of the environment that have an important cultural or historical signifcance when being used. Meanwhile, Wagman et al. (2016) suggest calling them *subordinate* and *superordinate* affordances, pointing to the connections between affordances of different levels: affordances at lower levels have means which allow higher level affordances to come into existence.

In order to trace the relationships between different levels of affordances, Gaver (1991, 82) suggests dividing affordances into *sequential* and *nested*, where the former emerge as a result of actions on perceptible affordances (Gaver 1991, 82) while the latter refer to affordances that serve as a context for other affordances. The best example for sequential affordances can be the functions that a user learns about when logged in as an editor or a page administrator. In such case, each affordance that emerges after logging in would be a sequential affordance. Nested affordances are actualized in temporal sequences as well, "yet time is not the sole basis for the nesting of affordances" as "nesting can also exist across levels that differ in order" (Wagman et al. 2016, 2).

Studying affordances is essential for understanding archival composition, which is in turn pivotal for comprehending why some documents are included while others are excluded or censored. Archival composition refects biases of an archivist and/or donor, providing substantial information about societal, political and cultural contexts of the archives and in turn can shed light on degrees of participation in a given society.

Two key principles of archival practices—provenance and authenticity—help to unpack the composition of archives. In archival studies, while "provenance refers to the documentation of the origins and history of an archived item, authenticity denotes the preservation of the original object rather than the truth or accuracy of its content" (Kallinikos et al. 2013, 361). Both principles are important when it comes to the discussion of an archive's possibility to evoke multi-vocal narratives. As historian Jane Stevenson (2013, 160; 170) puts it, archives hardly ever store enough material to fully reconstruct the whole life of a person; therefore, it is crucial to know the origins of the available documents as well as their history to be able to construct narratives that would give the fullest picture of the subject in question.

The principles of provenance and authenticity are challenged in the digital environment because it is diffcult to trace the origins of the documents (Marton 2010). This diffculty arises when one gets into contact with digital copies, which usually have neither traces of materiality nor records about their inquisition. In other words, this diffculty is a result of the technological and organizational constraints (negative affordances) of the modern digital platforms that collect and make available historical documents.

## 21.3 Methodological Framework and Steps to Unpack *Prozhito* Archive

In order to learn what affordances an environment can offer, one has to engage with this environment. Activity theory, for example, postulates that environments can only be perceived through acting (Albrechtsen 2001). When acted upon, an environment reveals its hidden structures and its constraints as well as what are called *perceived* and *actual affordance*s, where the frst type stands for what a subject thinks he/she can do and the second for what a subject can actually do with/in the given environment (Norman 1988). Hence, in order to learn about affordances of digital archives, one has to try them out.

Taking off from the activity theory, Turner's simple and complex affordances (2005) and Gibson's (1979) positive affordances and constraints, the project investigates what actions are allowed and not allowed on *Prozhito*. First, the user interface was browsed to collect as much information as possible about the perceived and simple affordances of the platform. Second, the platform was tested in order to create a historical narrative. Preparing for the publication of a special issue of the journal *Baltic Worlds* dedicated to the Centenary of the Russian Revolution, the author of the chapter has used *Prozhito* to tell a story about the Russian Revolution from the perspective of its contemporaries. In order to do that diaries tagged with the year 1917 were selected for the analysis and publication (Kalinina and Kochergan 2018). To be able to speak about volunteer experiences, the author joined the community of one of the laboratories as well as followed some of the laboratories online. The choice of the type of participation was defned by the author's experiences and capabilities. Next, in order to learn more about the archival composition of *Prozhito*, the author interviewed the founders of the project Mikhail Melnichenko (2017) and Ilya Venyavkin (2017) as the information on the website was not suffcient despite a very encompassing description in the section "About the project" (*O proekte—*in Russian).

## 21.4 Unpacking *Prozhito*