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

Abstract

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.

Facebook and virtual nationhood: social media and the Arab Canadians community

“…Since part of this study is focused on understanding the online reactions of the online community, sentiment analysis becomes a suitable method here especially that the data set is large, and it is difficult as well as time consuming to manually code all the Facebook posts and comments. The sentiment analysis approach was used by many scholars cited below who wanted to understand the general sentiments towards different issues such as the online self-representation of the Tea Party Patriots in the USA and the Party for Freedom in the Netherlands (Groshek and Engelbert 2013), citizens' political preferences in Italy and France (Ceron et al 2014), predictions of general elections (Tumasjan et al 2010), sentiments towards the U.S. presidency (Hopkins and King 2010), and how newspapers and blogs cover events while expressing attitudes towards certain figures and/or places (Godbole et al 2007). Yet, the majority of previous studies were confined to Twitter (Go et al 2009;Pak and Paroubek 2010;Kouloumpis et al 2011;Agarwal et al 2011), while sentiment analysis studies involving Arabic or Facebook (see for example Neri et al 2012; Al-Rawi 2017a) are rare.…”

Mídias sociais e administração pública: análise do sentimento social perante a atuação do Governo Federal brasileiro

“…Primeiramente, esses resultados revelam a opinião dos cidadãos que são usuários das mídias sociais investigadas e que fizeram comentários sobre os temas definidos neste estudo durante dois períodos distintos de 30 dias. Dessa forma, é inadequado generalizar os números aqui apresentados em situações que ultrapassem esse espaço temporal e o universo de usuários, que não são, necessariamente, representativos da população de um país (CERON et al, 2014). Outra limitação é a impossibilidade de identificar, por meio da mineração de opinião automatizada, a que grupo social pertencem os usuários das mídias sociais analisadas neste estudo, uma vez que elas não disponibilizam informações sobre o perfil socioeconômico de seus usuários.…”

Data properties and the performance of sentiment classification for electronic commerce applications

“…Customer review data can be used for development of market strategy and decision making for product/ service requirements for customer satisfaction, strategic analysis, and commercial planning Ye et al 2009;Li and Wu 2010;Yu et al 2013;Kang and Park 2014;Meisel and Mattfeld 2010;Yan et al 2015;García-Moya et al 2013). Government and public sector can also take advantages of analysing public sentiment from their blog and social media to obtain citizen feedback on new policy implementation (Ceron et al 2014;Cheong and Lee 2011).…”