Whether Information Network Supplements Friendship Network

TL;DR

This study investigates how users' taste-related behavioral information influences friendship prediction in multi-relationship networks, revealing that taste similarity, especially involving popular objects, significantly improves friendship prediction accuracy.

Contribution

It analyzes the impact of behavioral taste information on friendship prediction, addressing the previously overlooked inverse relationship and discussing its contradiction with prior findings.

Findings

Taste similarity strongly correlates with friendship formation.

Behavioral information involving popular objects enhances prediction performance.

Contradicts prior work suggesting popularity-based taste information is redundant.

Abstract

Homophily is a significant mechanism for link prediction in complex network, of which principle describes that people with similar profiles or experiences tend to tie with each other. In a multi-relationship network, friendship among people has been utilized to reinforce similarity of taste for recommendation system whose basic idea is similar to homophily, yet how the taste inversely affects friendship prediction is little discussed. This paper contributes to address the issue by analyzing two benchmark datasets both including user's behavioral information of taste and friendship based on the principle of homophily. It can be found that the creation of friendship tightly associates with personal taste. Especially, the behavioral information of taste involving with popular objects is much more effective to improve the performance of friendship prediction. However, this result seems to be contradictory to the finding in [Q.M. Zhang, et al., PLoS ONE 8(2013)e62624] that the behavior information of taste involving with popular objects is redundant in recommendation system. We thus discuss this inconformity to comprehensively understand the correlation between them.