Enthusiasm and support: Alternative sentiment classification for social movements on social media

Shubhanshu Mishra, Kirstin Phelps, Sneha Agarwal, Johna Picco, Jinlong Guo, Jana Diesner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationWebSci 2014 - Proceedings of the 2014 ACM Web Science Conference
PublisherAssociation for Computing Machinery
Pages261-262
Number of pages2
ISBN (Print)9781450326223
DOIs
StatePublished - Jan 1 2014
Event6th ACM Web Science Conference, WebSci 2014 - Bloomington, IN, United States
Duration: Jun 23 2014Jun 26 2014

Publication series

NameWebSci 2014 - Proceedings of the 2014 ACM Web Science Conference

Other

Other6th ACM Web Science Conference, WebSci 2014
CountryUnited States
CityBloomington, IN
Period6/23/146/26/14

Keywords

  • Data classification
  • Data corpus
  • Human factors
  • Social causes
  • Social network analysis

ASJC Scopus subject areas

  • Computer Networks and Communications

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