Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

8-2013

Abstract

In political contexts, it is known that people act as "motivated reasoners", i.e., information is evaluated first for emotional affect, and this emotional reaction influences later deliberative reasoning steps. As social media becomes a more and more prevalent way of receiving political information, it becomes important to understand more completely the interaction between information, emotion, social community, and information-sharing behavior. In this paper, we describe a high-precision classifier for politically-oriented tweets, and an accurate classifier of a Twitter user's political affiliation. Coupled with existing sentiment-analysis tools for microblogs, these methods enable us to systematically study the interaction of emotion and sharing in a large corpus of politically-oriented microblog messages, collected from just before the 2012 US presidential election. In particular, we seek to understand how information sharing is influenced by the political affiliation of the sender and receiver of a message, and the sentiment associated with the message.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Influence and Political Communication | Social Media

Publication

Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining: ASONAM 2013: Niagara Falls, 25-28 August 2013

First Page

282

Last Page

289

ISBN

9781450322409

Identifier

10.1145/2492517.2492554

Publisher

ACM

City or Country

New York

Copyright Owner and License

LARC

Additional URL

http://doi.org/10.1145/2492517.2492554

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