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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 2023
dc.identifier.citation Schöll N, Gallego A, Le Mens G. How politicians learn from citizens' feedback: the case of gender on Twitter. American Journal of Political Science. 2023 Mar 22. DOI: 10.1111/ajps.12772
dc.identifier.issn 0092-5853
dc.identifier.uri http://hdl.handle.net/10230/56344
dc.description Data de publicació electrònica: 22-03-2023
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.language.iso eng
dc.publisher Wiley
dc.relation.ispartof American Journal of Political Science. 2023 Mar 22
dc.relation.isreferencedby http://dx.doi.org/10.7910/DVN/DWYLME
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.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.identifier.doi http://dx.doi.org/10.1111/ajps.12772
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.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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