A Visibility-based Model for Link Prediction in Social Media

TitleA Visibility-based Model for Link Prediction in Social Media
Publication TypeConference Paper
Year of Publication2014
AuthorsL. Zhu, and K. Lerman
Conference NameProceedings of the ASE/IEEE Conference on Social Computing

A core task of social network analysis is to predict the formation of new social links. In the context of social media, link prediction serves as the foundation for forecasting the evolution of the follower graph and predicting interactions and the flow of information between users. Previous link prediction methods have generally represented the social network as a graph and leveraged topological and semantic measures of similarity between two nodes to evaluate the probability of link formation. In this work, we suggest another link creation mechanism for social media wherein a user v creates a link to user u after seeing u