achieve the highest AUC score of 0.88 from our multilayer features set, *proving the multilayer construct a useful tool for social bootstrapping and friend recommendations*.

The remainder of this work details these contributions, and summarises related work, concluding with a discussion of the implications, limitations, and applications of the proposed framework.

Related Work
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Our work identifies with three main areas: multi-relational social networks, media multiplexity, and link prediction in online social networks. We summarise the state of the art in these areas in the following sections.

Multilayer Social Networks
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Multi-relational or multilayer networks have been explored in the context of a wide range of systems from global air transportation [@cardillo2013] to massive online multiplayer games [@Szell19072010]. A comprehensive review of multilayer network models can be found in [@kivela2013]. In the context of social networks, it is generally accepted that the more information we can obtain about the relationship between people, the more insight we can gain. A recent large-scale study on the subject has demonstrated the need for multi-channel data when comprehensively studying social networks [@lehman2014]. Despite the observable multilayer nature of the composite OSNs of users [@kivela2013; @kazienko2010; @brodka2012], most research efforts have been focused on theoretical 