Just Published! Social media electoral forecast: State-of-the-art

home_cover

Using Social Media to Forecast Electoral Results: A Review of the State of the Art

Italian Journal of Applied Statistics – Statistica Applicata

Co-authors: Luigi Curini & Stefano M. Iacus

Replication material: andreaceron.com/publications

Acknowledgments: Voices from the Blogs for providing data

What is worth remembering:

  • Many scholars tried to predict elections using social media
  • Some methods are better than others
  • Supervised sentiment analysis seems the best choice
  • Predictions are more accurate in countries with Proportional Representation

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.

Just Published! (Positive and Negative) E-campaigning on Twitter in the 2013 Italian election

home_cover

E-campaigning on Twitter: The effectiveness of distributive promises and negative campaign in the 2013 Italian election

New Media & Society (Journal IF: 2.052)

Co-author: Giovanna d’Adda

Replication material: andreaceron.com/publications

Acknowledgments: Voices from the Blogs; Alessandra Cremonesi; University of Birmingham

What is worth remembering:

  • Analysis of Twitter useful to investigate electoral campaign effects
  • Voting intentions on Twitter react to real events of the campaign
  • Negative campaign effective against rival adjacent parties
  • Negative campaign more effective when the attacker is under attack (voters close ranks!)
  • Negative campaign = more votes for PD (+1.31%) rather than PDL (+0.22%)
  • Distributive promises effective only when properly targeted
  • Distributive promises = more votes for Berlusconi’s PDL (+0.12%) but less for PD (-0.42%)
  • More “Spread” = more votes for Grillo’s M5S (+0.37%) and less for PD (-0.52%)

Abstract

Recent studies investigated the effect of e-campaigning on the electoral performance. However, little attention has been paid to the content of e-campaigning. Given that political parties broadcast minute-by-minute the campaign messages on social media, this comprehensive and unmediated information can be useful to evaluate the impact of different electoral strategies. Accordingly, this article examines the electoral campaign for the 2013 Italian general election to assess the effectiveness of positive and negative campaigning messages, measured through content analysis of information published on the official Twitter accounts of Italian parties. We evaluate their impact on the share of unsolicited voting intentions expressed on Twitter, measured through an innovative technique of sentiment analysis. Our results show that negative campaign has positive effects and its impact is stronger when the attacker is meanwhile under attack. Conversely, we only find a circumstantial effect of positive campaign related to clientelistic and distributive appeals.