Title
Finding Credible Information Sources in Social Networks Based on Content and Social Structure
Abstract
A task of primary importance for social network users is to decide whose updates to subscribe to in order to maximize the relevance, credibility, and quality of the information received. To address this problem, we conducted an experiment designed to measure the extent to which different factors in online social networks affect both explicit and implicit judgments of credibility. The results of the study indicate that both the topical content of information sources and social network structure affect source credibility. Based on these results, we designed a novel method of automatically identifying and ranking social network users according to their relevance and expertise for a given topic. We performed empirical studies to compare a variety of alternative ranking algorithms and a proprietary service provided by a commercial website specifically designed for the same purpose. Our findings show a great potential for automatically identifying and ranking credible users for any given topic.
Year
DOI
Venue
2011
10.1109/PASSAT/SocialCom.2011.91
2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing
Keywords
DocType
ISBN
information source,content structure,social structure,information relevance,information credibility,information quality,credibility judgment,source credibility,social network user identification,social network user ranking
Conference
978-1-4577-1931-8
Citations 
PageRank 
References 
43
1.74
8
Authors
3
Name
Order
Citations
PageRank
Kevin Robert Canini1726.66
Bongwon Suh22203171.49
Peter Pirolli33661538.83