Social Network Model based on Keyword Categorization

A user profile on an online social network is characterized by its profile entries (keywords). In this paper, we study the relationship between semantic similarity of user keywords and the social network topology. First, we present a 'forest' model to categorize keywords and define the notion of distance between keywords across multiple categorization trees (i.e., a forest). Second, we use the keyword distance to define similarity functions between a pair of users and show how social network topology can be modeled accordingly. Third, we validate our social network topology model, using a simulated social graph, against a real life social graph dataset.