Friendship prediction and homophily in social media
ABSTRACT
Social media have attracted considerable attention because their open-ended nature allows users to create lightweight semantic scaffolding to organize and share content. To date, the interplay of the social and topical components of social media has been only partially explored. Here we study the presence of homophily in three systems - Flickr, Last.fm and Anobii - that combine tagging of social media with online social networks. We find a substantial level of topical similarity among users who lie close to each other in the social network. We introduce a null model that preserves user activity while removing local correlations, allowing us to disentangle the actual local similarity between users from statistical effects due to the assortative mixing of user activity and centrality in the social network. This analysis suggests that social networks constructed from topical similarity capture actual friendship accurately and that topical similarity can achieve a link prediction accuracy of 92% when combined with topological features.
AUTHORS: Rossano Schifanella
WHEN: Thusday, May 31th, 2011, 13:00
WHERE: Sala Congressi Pier della Francesca
DATE-TAG:2011
- Individual Seminars (IS)