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Title:Enthusiasm And Support: Alternative Sentiment Classification For Social Movements On Social Media
Author(s):Mishra, Shubhanshu; Agarwal, Sneha; Guo, Jinlong; Phelps, Kirstin; Picco, Johna; Diesner, Jana
Subject(s):Sentiment Analysis
Social Network Analysis
Abstract:We present a novel sentiment classifier particularly designed for modeling and analyzing social movements; capturing levels of support (supportive versus non-supportive) and degrees of enthusiasm (enthusiastic versus passive). The resulting computational solution can help organizations involved with social causes to disseminate messages in a more informed and effective fashion; potentially leading to greater impact. Our findings suggest that enthusiastic and supportive tweets are more prevalent in tweets about social causes than other types of tweets on Twitter.
Issue Date:2014-06
Publisher:ACM Digital Library
Citation Info:Shubhanshu Mishra, Sneha Agarwal, Jinlong Guo, Kirstin Phelps, Johna Picco, and Jana Diesner. 2014. Enthusiasm and support: alternative sentiment classification for social movements on social media. In Proceedings of the 2014 ACM conference on Web science (WebSci '14). ACM, New York, NY, USA, 261-262. DOI=10.1145/2615569.2615667
Genre:Conference Poster
Publication Status:published or submitted for publication
Peer Reviewed:is peer reviewed
Date Available in IDEALS:2014-06-29

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