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Computing Distrust in Social Media

Abstract A myriad of social media services are emerging in recent years that allow people to communicate and express themselves conveniently and easily. The pervasive use of social media generates massive data at an unprecedented rate. It becomes increasingly difficult for online users to find relevant information or, in other words, exacerbates the information overload problem. Meanwhile, users in social media can be both passive content consumers and active content producers, causing the quality of user-generated content can vary dramatically from excellence to abuse or spam, which results in a problem of information credibility. Trust, providing evidence about with whom users can trust to share information and from whom users can accept informati... (more)
Created Date 2015
Contributor Tang, Jiliang (Author) / Liu, Huan (Advisor) / Xue, Guoliang (Committee member) / Ye, Jieping (Committee member) / Aggarwal, Charu (Committee member) / Arizona State University (Publisher)
Subject Computer science / Applying Distrust / Distrust / Negative Links / Predicting Distrust / Signed Social Networks / Understanding distrust
Type Doctoral Dissertation
Extent 130 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Computer Science 2015
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis