Accession Number : AD1007379


Title :   Computing Distrust in Social Media


Descriptive Note : Technical Report


Corporate Author : Arizona State University Tempe United States


Personal Author(s) : Tang,Jiliang


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1007379.pdf


Report Date : 01 May 2015


Pagination or Media Count : 132


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 information without additional verification, plays a crucial role in helping online users collect relevant and reliable information. It has been proven to be an effective way to mitigate information overload and credibility problems and has attracted increasing attention.


Descriptors :   social media , algorithms , Mathematical prediction


Distribution Statement : APPROVED FOR PUBLIC RELEASE