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University of Cambridge > Talks.cam > Wednesday Seminars - Department of Computer Science and Technology > Every tweet counts: How statistical content analysis of social networks can improve our knowledge of citizens' preferences. An application to France and US presidential elections and EU leaders' popularity
Every tweet counts: How statistical content analysis of social networks can improve our knowledge of citizens' preferences. An application to France and US presidential elections and EU leaders' popularityAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Stephen Clark. 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. This talk is part of the Wednesday Seminars - Department of Computer Science and Technology series. This talk is included in these lists:
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