Characterizing swing voters in online social media: the case of the 2022 Italian elections

Abstract The global proliferation of social media platforms has transformed political communication, making the study of online interactions between politicians and voters crucial for understanding contemporary political discourse. In this work, we present a methodological framework for modeling and examining the dynamics of political messaging and voter behavior in online social media. We propose a nuanced categorization of voters who changed their political preferences over time (i.e., swing voters) based on their shifting patterns, as well as a characterization of their susceptibility to propaganda messages. Drawing on the case of the 2022 Italian elections on Twitter, our analysis reveals that during election periods, politicians’ popularity increases, accompanied by notable variations in the use of persuasive language techniques, including doubt, loaded language, appeals to values, and slogans. Swing voters demonstrate higher vulnerability to these propaganda techniques compared to non-swing voters, with distinct vulnerability patterns across various types of political shifts. These findings highlight the nuanced impact of social media on political opinion formation, contributing to a deeper understanding of the interplay between digital political communication and online voter behavior in contemporary democracies.

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Publication Details

Journal
Social Network Analysis and Mining
Published
2025-07-26
DOI
https://doi.org/10.1007/s13278-025-01457-4
Citations
1
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
4.20

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article

Characterizing swing voters in online social media: the case of the 2022 Italian elections

Alessia Antelmi, Arianna Pera, Lucio La Cava
1 citations
Social Network Analysis and Mining
Misinformation and Its Impacts
4.20
article

Characterizing swing voters in online social media: the case of the 2022 Italian elections

Alessia Antelmi, Arianna Pera, Lucio La Cava
article en
1 citations

Abstract

Abstract The global proliferation of social media platforms has transformed political communication, making the study of online interactions between politicians and voters crucial for understanding contemporary political discourse. In this work, we present a methodological framework for modeling and examining the dynamics of political messaging and voter behavior in online social media. We propose a nuanced categorization of voters who changed their political preferences over time (i.e., swing voters) based on their shifting patterns, as well as a characterization of their susceptibility to propaganda messages. Drawing on the case of the 2022 Italian elections on Twitter, our analysis reveals that during election periods, politicians’ popularity increases, accompanied by notable variations in the use of persuasive language techniques, including doubt, loaded language, appeals to values, and slogans. Swing voters demonstrate higher vulnerability to these propaganda techniques compared to non-swing voters, with distinct vulnerability patterns across various types of political shifts. These findings highlight the nuanced impact of social media on political opinion formation, contributing to a deeper understanding of the interplay between digital political communication and online voter behavior in contemporary democracies.

Social Network Analysis and MiningVol. 15(1)
University of Calabria (IT), University of Turin (IT), IT University of Copenhagen (DK)
European Commission, Università degli Studi di Torino
Openalex Percentile: Top 7%
Misinformation and Its Impacts
4.20
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Characterizing swing voters in online social media: the case of the 2022 Italian elections — Alessia Antelmi, Arianna Pera, et al. · Social Network Analysis and Mining (2025) | TGRS Research Map | TGRS