Recommendation Actively Utilizing User's Network of Trust
Danielle Hyunsook Lee, Peter L. Brusilovsky · D-Scholarship@Pitt (University of Pittsburgh) · 2009
In collaborative filtering recommender systems, users cannot get involved in the choice of their peer group. It leaves users defenseless against various spamming or “shilling” attacks. Other social Web-based systems, however, allow users to self-select trustworthy peers and build a network of trust. We argue that users self-defined networks of trust could be valuable to increase the quality of recommendation in CF systems. To prove the feasibility of this idea we examined how similar are interests of users connected by a self-defined relationship in a social Web system, CiteuLike. Interest similarity was measured by similarity of items and meta-data they share. Our study shows that users connected by a network of trust exhibit significantly higher similarity on items and meta-data than non-connected users. This similarity is highest for directly connected users and decreases with the increase of distance between users.