University Of Tasmania

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Combining activity-evaluation information with NMF for trust-link prediction in social media

conference contribution
posted on 2023-05-23, 11:14 authored by Matsutani, K, Kumano, M, Kimura, M, Saito, K, Ohara, K, Motoda, H
Acquiring a network of trust relations among users in social media sites, e.g., item-review sites, is important for analyzing users' behavior and efficiently finding reliable information on the Web. We address the problem of predicting trustlinks among users for an item-review site. Non-negative matrix factorization (NMF) methods have recently been shown useful for trust-link prediction in such a site where both link and activity information is available. Here, a user activity in an item-review site means posting a review and giving a rating for an item. In this paper, for better trust-link prediction, we propose a new NMF method that incorporates people's evaluation of users' activities as well as trust-links and users' activities themselves. We further apply it to an analysis of users' behavior. Using two real world item-review sites, we experimentally demonstrate the effectiveness of the proposed method.


Publication title

Proceedings of the 2015 IEEE International Conference on Big Data


H Ho, BC Ooi, MJ Zaki, X Hu, L Haas, V Kumar, S Rachuri, S Yu, M Hui-Hsiao, J Li, F Luo, S Pyne, K O






School of Engineering


IEEE-Inst Electrical Electronics Engineers Inc

Place of publication

United States of America

Event title

2015 IEEE International Conference on Big Data

Event Venue

Santa Clara, CA, USA

Date of Event (Start Date)


Date of Event (End Date)


Rights statement

Copyright 2015 IEEE

Repository Status

  • Restricted

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