Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens’ political preferences with an application to Italy and France

By Andrea Ceron, Luigi Curini, Stefano Maria Iacus, Giuseppe Porro. New Media & Society, 2013

513 citations recorded by the source corpus.

The growing usage of social media by a wider audience of citizens sharply increases the possibility of investigating the web as a device to explore and track political preferences. In the present paper we apply a method recently proposed by other social scientists to three different scenarios, by analyzing on one side the online popularity of Italian political leaders throughout 2011, and on the other the voting intention of French Internet users in both the 2012 presidential ballot and the subsequent legislative election. While Internet users are not necessarily representative of the whole population of a country’s citizens, our analysis shows a remarkable ability for social media to forecast electoral results, as well as a noteworthy correlation between social media and the results of traditional mass surveys. We also illustrate that the predictive ability of social media analysis strengthens as the number of citizens expressing their opinion online increases, provided that the citizens act consistently on these opinions.

Subfields: Communication, Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/6e76202727df5de1105a49b81768bc51d4ae8a77

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Citations in the corpus

Surpassing the Limit: Keyword Clustering to Improve Twitter Sample Coverage (2015, background): “Other efforts have also shown promising results by using social media to discover a wide range of collective knowledge such as real-time political polling [4, 22] and the potential success of movies at box-office [2, 14].”
On Unravelling Opinions of Issue Specific-Silent Users in Social Media (2016, background): “…2009 (Tumasjan et al. 2010), US Senate special Election in Massachusetts 2010 (Chung and Mustafaraj 2011), Dutch Senate Election in 2011 (Sang and Bos 2012), Irish General Election in 2011 (Bermingham and Smeaton 2011) and French Presidential and Legislative Elections in 2012 (Ceron et al. 2014).”
A Meta-Analysis of State-of-the-Art Electoral Prediction From Twitter Data (2012, methodology): “Except for Bermingham and Smeaton (2011), Tjong Kim Sang and Bos (2012), and Ceron et al. (2013) who applied supervised sentiment analysis—with mixed results, it must be said—the rest of the studies have relied on lexicons to determine the polarity of tweets.”
Fake News Identification on Twitter with Hybrid CNN and RNN Models (2018, unknown): “[4] For example, in France and Italy, even though internet users may not accurately represent the demographics of the entire population, opinions on social media and mass surveys of citizens are correlated.”