forms were manually reviewed and manually translated[^18]. When available, dictionaries were completed using precompiled lists existing in the Web.

Emoticon lexicon is a dictionary of regular expression matching a number of emoticons to their corresponding sentiment in the aforementioned scale.

Lastly, stopword lemma lists are used to discard most frequent lemmas when extracting n-gram features from texts. We adapted this lists to SA requirements by removing some lemmas, because of their relevance to polarity classification (e.g., no, good, ...).

  ------------------------ ----------------------------------------------------- --------- --------- -------- ---------
  [**Resource**]{}         [**Use**]{}                                                                        
                                                                                    eu        es        en       fr
  Word form dictionaries   text normalization (e.g. 4ever$\rightarrow$forever)    122,085   556,501   67,811   453,037
  OOV dictionaries         text normalization (e.g. 4ever$\rightarrow$forever)      63       7,823     223       279
  Emoticon lexicon         Polarity tagging                                                                   
  Stopword lemma lists     Polarity tagging feature extraction                      56        46        75       100
  ------------------------ ----------------------------------------------------- --------- --------- -------- ---------

NLP pre-processing {#isv2018:da:ixa-pipes}
------------------

EliXa currently performs tokenization, lemmatization and POS tagging prior to sentiment analysis classification. No entity recognition is applied; entities are matched only if they are defined as keywords. Although EliXa is able to work with corpora preprocessed with other taggers, its default NLP processing is made by means of IXA pipes [@agerri2014ixapipes] which is integrated as a library.

Sentiment Analysis {#isv2018:da:elixa}
------------------

EliXa’s 