https://orcid.org/0000-0002-4473-8360
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ABSTRACT
The present study addresses the effect of the discourse of elites on Twitter on citizens’ affective polarisation through a quasi-experiment that was embedded in a survey panel. Participants were invited to follow one of the Twitter accounts of nine candidates from the main political parties during the 2019 European Parliament electoral campaign in Spain. Experiment compliance among participants was confirmed using web-tracking data (passive metre). The results show that exposure to candidates’ Twitter accounts by self-selection does not increase affective polarisation. Although high levels of polarisation might contribute to building echo chambers, the polarising content contained in the partisan Twitter accounts has no effect on increasing affective polarisation, even among those who strongly identify with such parties. This finding confirms the so-called limited media effect hypothesis for social media.
Supplemental data
Supplementary data for this article can be accessed at https://doi.org/10.1080/13608746.2022.2047554.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. In Spain, Election Day was 26 May.
2. Question p19a_4 in the codebook of the dataset.
3. Those are as follow:
Anti-Catalan – ‘independentis*’, ‘criminal’, ‘separatis*’, ‘henchmen’, ‘want to break Spain’ and ‘seccesion*’;
Pro-Catalan – ‘freedom fighters’, ‘our country’, ‘state recognition’, ‘proud of being Catalan’, ‘proud of our land’, ‘the fight will make us free’ and ‘long live Catalonia’;
Anti-Spanish – ‘from the exile’, ‘exiles’, ‘Spanish injustice’, ‘nondemocratic country’, ‘repress*’, ‘Spanish nationalists’, ‘totalitarians’ and ‘court prosecution’ and
Pro-Spanish – ‘proud to be Spanish’, ‘great Spain’, ‘Spaniards together are stronger’ and ‘long live Spain’.
4. Negative expressions were coded as anti-partisan when attached to a clear reference to the name of the political party, either the long version or the acronym, political leaders or well-known members of their parties. In addition, we included regular expressions that were commonly employed in the media and among public opinion to refer to each party, such as ‘socialistas’ or ‘sociatas’ for PSOE; ‘comunistas’ for Unidas Podemos; ‘conservadores’ or ‘peperos’ for PP; ‘naranjas’ or ‘naranjito’ for Cs; ‘abertzales’ for EH-Bildu; ‘fachas’ or ‘fascist*’ for Vox; ‘separatis*’ ‘independentis*’ as an anti-partisan feeling against JxCat and ERC and ‘PPPSOE’ as a negative expression for both PP and PSOE.
5. To capture each respondent’s Twitter behaviour, we asked them in a previous survey for their usernames, collecting a total of 269 accounts. The resulted datasets have been completely anonymised using the respondent’s numerical id for the survey as the matching id; all traces of usernames (either ‘screen_name’ or ‘user_id’) have been deleted.
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Javier Lorenzo-Rodríguez
Javier Lorenzo-Rodríguez is a Visiting Professor of Political Science in the Department of Social Sciences at Universidad Carlos III of Madrid. European Ph.D. in Political Science (2012), he has been a research fellow at the NYU Centre of Social Media and Politics. His research focuses on applying computational methods to online political behaviour in Western democracies, mainly of candidates and political parties in competitive scenarios.
Mariano Torcal
Mariano Torcal is a Full Professor in Political Science and ICREA Research Fellow at the Department of Political and Social Science at the Pompeu Fabra University in Barcelona, and Director of the Research and Expertise Centre for Survey Methodology (RECSM). He has published articles on topics such as political disaffection, political trust and satisfaction with democracy, electoral behaviour, political participation and party system institutionalisation in major international journals.