Mining Public Opinion about Economic Issues: Twitter and the U.S. Presidential Election

Amir Karami, London S. Bennett and Xiaoyun He
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Amir Karami: School of Library and Information Science, University of South Carolina, Columbia, USA
London S. Bennett: University of South Carolina Honors College, Columbia, USA
Xiaoyun He: Department of Information Systems, Auburn University at Montgomery, Montgomery, USA

International Journal of Strategic Decision Sciences (IJSDS), 2018, vol. 9, issue 1, 18-28

Abstract: Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years, social media such as Twitter has enabled people to share their opinions regarding elections. Social media has provided a platform for collecting a large amount of social media data. This article proposes a computational public opinion mining approach to explore the discussion of economic issues in social media during an election. Current related studies use text mining methods independently for election analysis and election prediction; this research combines two text mining methods: sentiment analysis and topic modeling. The proposed approach has effectively been deployed on millions of tweets to analyze economic concerns of people during the 2012 US presidential election.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jsds00:v:9:y:2018:i:1:p:18-28

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