Investigating topic models for social media user recommendation

This paper presents a user recommendation system that recommends to a user new friends having similar interests. We automatically discover users’ interests using Latent Dirichlet Allocation (LDA), a linguistic topic model that represents users as mixtures of topics. Our system is able to recommend friends for 4 million users with high recall, outperforming existing strategies based on graph analysis. Categories and Subject Descriptors I.2.7 [Artificial Intelligence]: Natural Language Processing—language models General Terms Algorithms Keywords social media, user recommendation, topic models, LDA

• Type: Journal
• Year: 2011
• Where: WWW
• Authors: Marco Pennacchiotti, Siva Gurumurthy
• Keywords: Internet Technology, Latent Dirichlet Allocation, Topic Models, User Recommendation, WWW 2011