Improving political discourse analysis on Twitter with context analysis

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dc.contributor.authorBilbao Jayo, Aritz
dc.contributor.authorAlmeida, Aitor
dc.date.accessioned2025-09-08T17:20:16Z
dc.date.available2025-09-08T17:20:16Z
dc.date.issued2021-07-26
dc.date.updated2025-09-08T17:20:16Z
dc.description.abstractIn this study, we propose a new approach to perform political discourse analysis in social media platforms based on a widely used political categorisation schema in the field of political science, namely, the Comparative Manifestos Project's category schema. This categorisation schema has been traditionally used to perform content analysis in political manifestos, giving a code that indicates the domain or category of each of the phrases in the manifestos. Therefore, in this work we propose the application of this political discourse analysis technique in Twitter, using as training data of 100 publicly available annotated political manifestos in English with around 85,000 annotated sentences. Furthermore, we also analyse the improvement that using 5,000 annotated tweets could provide to the performance of the political discourse classifier already trained with political manifestos. Finally, we have analysed the 2016 United States presidential elections on Twitter using the proposed approach. As our main finding, we have been able to conclude that both datasets (political manifestos and annotated tweets) can be combined in order to achieve better results, achieving improvements in the F-Measure of more than 15 points. Moreover, we have also analysed if contextual information such as the previous tweet or the political affiliation of the transmitter could improve classifier's performance as it has already been proven for manifestos classification, introducing a novel method for political parties representation and finding that adding the previous tweet or the political leaning as contextual data does improve its performance.en
dc.description.sponsorshipThis work was supported in part by the Basque Government’s Department of Education for the Deustek Research Group under Grant IT 1078-16 D, and in part by the Spanish Ministry of Science, Innovation and Universities through the Project Midiendo la competición política de las elecciones autonómicas en programas y twitter and the 10 años de Regional Manifestos Project under Grant RTI2018-095918-B-I00.en
dc.identifier.citationBilbao-Jayo, A., & Almeida, A. (2021). Improving political discourse analysis on Twitter with context analysis. IEEE Access, 9, 104846-104863. https://doi.org/10.1109/ACCESS.2021.3099093
dc.identifier.doi10.1109/ACCESS.2021.3099093
dc.identifier.eissn2169-3536
dc.identifier.urihttps://hdl.handle.net/20.500.14454/3553
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subject.otherComputational linguistics
dc.subject.otherData analysis
dc.subject.otherMachine learning
dc.subject.otherNatural language processing
dc.subject.otherText analysis
dc.titleImproving political discourse analysis on Twitter with context analysisen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.endPage104863
oaire.citation.startPage104846
oaire.citation.titleIEEE Access
oaire.citation.volume9
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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