Folks in folksonomies: Social link prediction from shared metadata

Web 2.0 applications have attracted a considerable amount of 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 semantic components of social media has been only partially explored. Here we focus on Flickr and Last.fm, two social media systems in which we can relate the tagging activity of the users with an explicit representation of their social network. We show that a substantial level of local lexical and topical alignment is observable 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 alignment between users from statistical effects due to the assortative mixing of user activity and centrality in the social network. This analysis suggests that users with similar topical interests are more likely to be friends, and there...

• Type: Conference
• Year: 2010
• Where: WSDM
• Authors: Rossano Schifanella, Alain Barrat, Ciro Cattuto, Benjamin Markines, Filippo Menczer
• Keywords: Data Mining, Semantic Similarity Captures, Semantic Similarity Measures, Social Network, WSDM 2010