Data di Pubblicazione:
2013
Citazione:
Using social media to forecast electoral results: a review of the state of the art / A. Ceron, L. Curini, S.M. Iacus. - In: STATISTICA APPLICATA. - ISSN 1125-1964. - 25:3(2013), pp. 239-261.
Abstract:
The paper discusses the advantages of using Supervised Aggregated Sentiment Analysis (SASA) of social media to forecast electoral results and presents an extension of the ReadMe method (Hopkins and King, 2010), which is particularly suitable to addressing a large number of categories (e.g. parties) providing lower standard errors. We analyze the voting intention of social media users in several elections held between 2011 and 2013 in France, Italy, and the United States. We then compare 80 electoral forecasts made using these or other techniques of data-mining and sentiment analysis. The comparison shows that the choice of the method is crucial. Electoral forecasts are also more accurate in countries with higher Internet penetration and given the presence of electoral systems
based on proportional representation.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Electoral Forecast; Sentiment Analysis; Text Mining; Social Media; Twitter
Elenco autori:
A. Ceron, L. Curini, S.M. Iacus
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