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The Image of Politicians in Italy in the Context of COVID-19

Political Parties
Populism
Social Media
Big Data
Enzo Loner
Università degli Studi di Trento
Enzo Loner
Università degli Studi di Trento
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Abstract

This work focuses on the effects of covid-19 on the public image of Italian politicians. Secondly, it intends to understand whether the analysis of social messages related to the virus can provide useful information to track the appreciation of politicians in the population. The basic assumption is that social media messages conveying emotions can on the one hand provide a measure of the appreciation of leaders and, at the same time, help to form or undo popularity. These questions are relevant because Italy has been one of the countries most affected by the pandemic and the debate on the virus has dominated the speeches in social media. Themes such as the denial - at least initial - of the severity of the problem, the need (or not) to wear protective masks, closures and lockdown have gained great space and highlighted a deep rift in the country touching the political sphere. In this general context, almost a year after the outbreak of the pandemic, the popularity of parties and their leaders has changed. For example, the Lega Nord (LN) by Matteo Salvini, which at the end of 2019 enjoyed in the national polls a percentage of preferences around 35%, at the end of 2020 suffered a loss of over 10 points and was almost reached by the Democratic Party (PD, the main center-left party). Among the right-wing populist forces was the great advance of Fratelli d'Italia (FDI) by Giorgia Meloni. In the first part of the research were downloaded from Twitter all the messages containing the hashtags about the coronavirus posted in Italian between the discovery of "patient 1" (20 February 2020) and 31 December 2020 (over 1,600,000 tweets). Then, from the total number of tweets, was extracted and analysed the subset in which the names of the leaders of the main Italian political parties appeared (over 170,000 tweets). The analysis focused then on the words related to individual leaders and the trend in the period of time considered, as well as on the emotions and on the maps of the relationships (co-occurrences) between the words associated with each politician. Almost half of the tweets extracted cite Prime Minister Conte. Most of these messages relate to the anti-covid measures of the government and therefore assume a protective and positive connotation for Italians. This is also the case for the tweets containing the names of the representatives of the governing coalition parties: Zingaretti (PD), Di Maio (M5S) and Renzi (Italia Viva). Among the opposition parties, the leader of the LN, Salvini, is over-mentioned. Curiously, the leaders of the two right-wing populist parties, Salvini and Meloni, are often associated in their networks of words, but the words with negative meanings relate mainly to Salvini. Little mentioned in the tweets is the leader of Forza Italia Berlusconi. The results show that the analysis of the emotions and frames present in social media can be used as a proxy to detect the trend of popularity of political figures.