Abstract

The growing usage of internet and social media by a wider audience of citizens sharply increases the possibility to investigate the web as a device to explore and track their (policy) preferences and judgements. For the statistician social networks data are interesting for at least two reasons: users of social networks express mainly unsolicited opinions and the volume of these opinions is extremely high, i.e. this is the big data world. In the present talk we present the statistical ideas behind the so called Hopkins and King’s method for content analysis as well as several successful applications to politics and political competitions. As simple case studies, we present the results obtained by “Voices from the Blogs” (http://voicesfromtheblogs.com, a research project developed at the University of Milan) on the 2012 Presidential ballot and in the subsequent Legislative election, the recent US Presidential competition and EU leaders popularity. Despite internet users are not necessarily representative of the whole population of country’s citizens, our analyses show a remarkable ability of social-media to forecast electoral results as well as a consistent correlation between social-media results and the ones obtained in more traditional mass surveys. In some cases, the possibility of an ‘information overload’ arises as a factor affecting negatively the analysis of social-media.