Muppalla, Sai Eshwar Prasad
Examining Untempered Social Media: Information Mutation on GAB.ai
1 online resource (62 pages) : PDF
University of North Carolina at Charlotte
Online social media often mirrors the social phenomenon of "Chinese Whispers" where information mutates during dissemination.Many a time, Twitter and Facebook in conjunction with smaller "fringe" communities like Gab.ai, often echo perspectives to facts and many do so under the guise of "free speech". In this work, we propose a novel framework to examine the information mutation and in some cases online extremism using approximately 43 million posts (both original content and comments) from 450,000 users on Gab in conjunction with 3 million related blogs and news articles. We develop a system that mines the interaction between Gab and mainstream news media, when there is discourse commonality (for eg. during a shock event - say Unite the Right protests in Charlottesville during August 2017) and show evidence of how information mutates to the tune of the echoes within the Gab social system. To demonstrate our framework, we present two case studies of information mutation and online extremism, namely - the Charlottesville Unite the Right protests and the Pittsburgh synagogue shooting in October 2018. Particularly, in the context of the Pittsburgh shooting, we present a thorough analysis of content similar to that of the shooter and evolving narratives of distorted information.
CLUSTERINGGAB.AIINFORMATION MUTATIONNATURAL LANGUAGE PROCESSINGSTORY CHAININGTEXT SIMILARITY
Cukic, BojanLee, Minwoo
Thesis (M.S.)--University of North Carolina at Charlotte, 2018.
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