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We love rock 'n' roll: analyzing and predicting friendship links in Last.fm

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Published:22 June 2012Publication History

ABSTRACT

Music plays an important role in our everyday lives. Not surprisingly, shared musical taste is said to lead to social attraction. In this paper, we study in detail friendship links on the social music platform Last.fm, asking for similarities in taste as well as on demographic attributes and local network structure. On Last.fm, users connect to 'online' friends as usual, but also indicate strong 'real-life' friends by co-attending the same events. Thus, we can contrast these online ties with offline links of different strength. Complementing the analysis, we learn to predict both kinds of ties automatically, including public interaction data as additional relevant features. Our results emphasize the predictive power of the simple measure of mutual friends, while the indicative value of similarity on taste (though increasing with tie strength) is negligible.

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  • Published in

    cover image ACM Conferences
    WebSci '12: Proceedings of the 4th Annual ACM Web Science Conference
    June 2012
    531 pages
    ISBN:9781450312288
    DOI:10.1145/2380718

    Copyright © 2012 ACM

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    Publication History

    • Published: 22 June 2012

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