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 language | English (US) |
|---|---|
| Title of host publication | WebSci 2014 - Proceedings of the 2014 ACM Web Science Conference |
| Publisher | Association for Computing Machinery |
| Pages | 261-262 |
| Number of pages | 2 |
| ISBN (Print) | 9781450326223 |
| DOIs | |
| State | Published - Jan 1 2014 |
| Event | 6th ACM Web Science Conference, WebSci 2014 - Bloomington, IN, United States Duration: Jun 23 2014 → Jun 26 2014 |
Publication series
| Name | WebSci 2014 - Proceedings of the 2014 ACM Web Science Conference |
|---|
Other
| Other | 6th ACM Web Science Conference, WebSci 2014 |
|---|---|
| Country | United States |
| City | Bloomington, IN |
| Period | 6/23/14 → 6/26/14 |
Keywords
- Data classification
- Data corpus
- Human factors
- Social causes
- Social network analysis
ASJC Scopus subject areas
- Computer Networks and Communications
Fingerprint Dive into the research topics of 'Enthusiasm and support: Alternative sentiment classification for social movements on social media'. Together they form a unique fingerprint.
Datasets
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Tweet IDs annotated for enthusiasm and support towards social causes: CTE, cyberbullying, and LGBT
Mishra, S. (Creator), Agarwal, S. (Creator), Guo, J. (Creator), Phelps , K. (Creator), Picco, J. (Creator) & Diesner, J. (Creator), University of Illinois at Urbana-Champaign, May 15 2020
DOI: 10.13012/B2IDB-2603648_V1
Dataset