2018/03/12 by Ghazaleh Beigi, Huan Liu, Beigi, Ghazaleh +1
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Opinion Dynamics and Social Influence #Recommender Systems and Techniques #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1803.04514
openalex publication_date 2018/03/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The pervasive use of social media provides massive data about individuals' online social activities and their social relations. The building block of most existing recommendation systems is the similarity between users with social relations, i.e., friends. While friendship ensures some homophily, the similarity of a user with her friends can vary as the number of friends increases. Research from sociology suggests that friends are more similar than strangers, but friends can have different interests. Exogenous information such as comments and ratings may help discern different degrees of agreement (i.e., congruity) among similar users. In this paper, we investigate if users' congruity can be incorporated into recommendation systems to improve it's performance. Experimental results demonstrate the effectiveness of embedding congruity related information into recommendation systems.