Using Sentiment Analysis to Monitor Electoral Campaigns: Method Matters—Evidence From the United States and Italy. (February 2015)

• Record Type: Journal Article
• Authors: Ceron, Andrea; Curini, Luigi; Iacus, Stefano M.
• Is Part Of: Social science computer review. Volume 33:Number 1(2015:Feb.)
• Page Start: 3
• Page End: 20
• Publication Date: 2015-02
• Subjects: sentiment analysis -- text mining -- text analytics -- social media -- electoral forecast; Social sciences -- Data processing -- Periodicals; Computers -- Social aspects -- Periodicals; Microcomputers -- Periodicals; Sciences sociales -- Informatique -- Périodiques; Micro-ordinateurs -- Périodiques; 300.285
• DOI: 10.1177/0894439314521983
• Languages: English
• ISSNs: 0894-4393

Abstract

In recent years, there has been an increasing attention in the literature on the possibility of analyzing social media as a useful complement to traditional off-line polls to monitor an electoral campaign. Some scholars claim that by doing so, we can also produce a forecast of the result. Relying on a proper methodology for sentiment analysis remains a crucial issue in this respect. In this work, we apply the supervised method proposed by Hopkins and King to analyze the voting intention of Twitter users in the United States (for the 2012 Presidential election) and Italy (for the two rounds of the centre-left 2012 primaries). This methodology presents two crucial advantages compared to traditionally employed alternatives: a better interpretation of the texts and more reliable aggregate results. Our analysis shows a remarkable ability of Twitter to "nowcast" as well as to forecast electoral results.