How politicians learn from citizens' feedback: the case of gender on Twitter

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• dc.contributor.author Schöll, Nikolas
• dc.contributor.author Gallego Dobón, Aina
• dc.contributor.author Le Mens, Gaël
• dc.date.accessioned 2023-03-24T08:43:08Z
• dc.date.available 2023-03-24T08:43:08Z
• dc.date.issued 2024
• dc.description Includes supplementary materials: online appendix; replication file.
• dc.description.abstract This article studies how politicians react to feedback from citizens on social media. We use a reinforcement-learning framework to model how politicians respond to citizens’ positive feedback by increasing attention to better received issues and allow feedback to vary depending on politicians’ gender. To test the model, we collect 1.5 million tweets published by Spanish MPs over 3 years, identify gender-issue tweets using a deep-learning algorithm (BERT) and measure feedback using retweets and likes. We find that citizens provide more positive feedback to female politicians for writing about gender, and that this contributes to their specialization in gender issues. The analysis of mechanisms suggests that female politicians receive more positive feedback because they are treated differently by citizens. To conclude, we discuss implications for representation, misperceptions, and polarization.
• dc.description.sponsorship The research leading to these results has received financial support from the project “Local politicians: selection and performance (LEADERS)” (CSO2016-79569-P) to Aina Gallego and from the grants AEI/FEDER UE-PSI201675353, PID2019-105249GB-I00/AEI/10.13039/501100011033, #RYC-2014-15035 to Gaël Le Mens, funded by the Spanish Ministry for the Economy, Industry and Competitiveness. It also benefited from funding from ERC Consolidator Grant #772268 and BBVA Foundation Grant G999088Q to Gaël Le Mens.
• dc.format.mimetype application/pdf
• dc.identifier.citation Schöll N, Gallego A, Le Mens G. How politicians learn from citizens' feedback: the case of gender on Twitter. Am J Pol Sci. 2024 Apr;68(2):557-74. DOI: 10.1111/ajps.12772
• dc.identifier.doi http://dx.doi.org/10.1111/ajps.12772
• dc.identifier.issn 0092-5853
• dc.identifier.uri http://hdl.handle.net/10230/56344
• dc.language.iso eng
• dc.publisher Wiley
• dc.relation.ispartof American Journal of Political Science. 2024 Apr;68(2):557-74
• dc.relation.isreferencedby http://dx.doi.org/10.7910/DVN/DWYLME
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/772268
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/CSO2016-79569-P
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-105249GB-I00
• dc.rights © 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
• dc.subject.other Xarxes socials en línia
• dc.subject.other Ciutadania
• dc.subject.other Polítics
• dc.title How politicians learn from citizens' feedback: the case of gender on Twitter
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion