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Research Article

Winners or losers? Using Twitter to evaluate how the COVID-19 pandemic changed the images of political leaders in Italy

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Pages 450-467 | Received 19 Jul 2021, Accepted 19 Feb 2022, Published online: 07 Sep 2022
 

ABSTRACT

This work focuses on the consequences of Covid-19 for the public images of political leaders as they emerge from Twitter discourses in Italy. To that end, the research investigates the tweets of Italian citizens about the pandemic in 2020 to understand whether the messages related to the virus can provide helpful information to track support for politicians. These goals are relevant because we know little about how the images of political leaders change in times of crisis, and Italy has been one of the countries most affected by the pandemic. The threat of the virus and the search for protection should increase confidence in the Prime Minister and foster the ‘rally-round-the-flag’ effect. However, as the debate on the virus dominated posts on Twitter, populist leaders opposing the Government could have taken advantage of the emergency to criticize the Government and thus gain support. Further, there are various political parties in the country, including right-wing mainstream and populist parties. Moreover, populists are both in the opposition and in government. We find that the images of politicians are shaped according to their stances relating to the pandemic and the ideas they promote. As expected, right-wing populists tried to use Twitter to criticize the Government but were often criticized for being ‘political looters’. Fear of the pandemic boosted confidence in the Prime Minister and his coalition. To understand these results, both context and the actor’s position are critical elements when studying public opinion through social media communication.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

3. The hashtags used were #coronavirus, #covid, #coronavid19, #coronavirusitalia, #covid19italia, and #covid2019. Re-tweets were excluded.

4. This result was checked from the survey trend published on www.scenaripolitici.com (as of January 2022).

5. Data from Wearesocial (2020), Digital 2020 Italia, https://wearesocial.com/it/blog/2020/01/digital-2020-italia/and www.oberlo.it. Accessed 26 November 2021.

6. In the figure, min.freq. indicates the minimum number of occurrences to include a word within the network. The co-occurrences for two words were measured using Pearson’s phi coefficient.

Additional information

Notes on contributors

Enzo Loner

Enzo Loner PhD. Expert in social research and data analysis. Research Assistant at University of Trento (Italy). His interests include public opinion, political sociology, environmental sociology and science in society.

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