#Criming and #Alive: Network and content analysis of two sides of a story on twitter. Issue 1 (2015)

• Record Type: Journal Article
• Authors: Kitzie, Vanessa; Ghosh, Debanjan
• Is Part Of: Proceedings of the Association for Information Science and Technology. Volume 52:Issue 1(2015)
• Page Start: 1
• Page End: 10
• Publication Date: 2015
• Subjects: Twitter -- race -- network -- topic model -- sentiment analysis; Information science -- Congresses; Information technology -- Congresses; Information science; Information technology; Conference papers and proceedings; 020
• DOI: 10.1002/pra2.2015.145052010041
• Languages: English
• ISSNs: 2373-9231

Abstract

ABSTRACT: On December 3, 2014, after a grand jury decided not to indict the white police officer in the death of Eric Garner, the social networking platform Twitter was flooded with tweets sharing stances on racial profiling and police brutality. To examine how issues concerning race were communicated and exchanged during this time, this study compares differences between tweets using two trending hashtags #CrimingWhileWhite (#cww) and #AliveWhileBlack (#awb) from December 3 through December 11, 2014. To this end, network and content analysis are used on a large dataset of tweets containing the hashtags #awb and #cww. Findings indicate that there are clear differences, both structurally and in linguistic style, between how individuals express themselves based on which hashtag they used. Specifically, we found that #cww users disproportionately shared informational content, which may have led to the hashtag gaining more network volume and attention as a trending topic than #awb. In contrast, #awb tweets tended to be more subjective, expressing a sense of community and strong negative sentiment toward persistent structural racism.