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The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweets
dc.contributor.author | Vilares, David | |
dc.contributor.author | Thelwall, Mike | |
dc.contributor.author | Alonso, Miguel A. | |
dc.date.accessioned | 2024-01-18T17:01:27Z | |
dc.date.available | 2024-01-18T17:01:27Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Vilares, D., Thelwall, M., & Alonso, M. A. (2015). The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweets. Journal of Information Science, 41(6), 799-813. https://doi.org/10.1177/0165551515598926 | es_ES |
dc.identifier.issn | 0165-5515 | |
dc.identifier.issn | 1741-6485 | |
dc.identifier.uri | http://hdl.handle.net/2183/34991 | |
dc.description | This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. This version of the article: Vilares, D., Thelwall, M., & Alonso, M. A. (2015). ‘The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweets’ has been accepted for publication in Journal of Information Science, 41(6), 799-813. Copyright © 2015 The Authors. DOI: https://doi.org/10.1177/0165551515598926. | es_ES |
dc.description.abstract | [Abstract]: Twitter is an important platform for sharing opinions about politicians, parties and political decisions. These opinions can be exploited as a source of information to monitor the impact of politics on society. This article analyses the sentiment of 2,704,523 tweets referring to Spanish politicians and parties from a month in 2014–2015. The article makes three specific contributions: (a) enriching SentiStrength, a fast unsupervised sentiment strength detection system, for Spanish political tweeting; (b) analysing how linguistic phenomena such as negation, idioms and character duplication influence Spanish sentiment strength detection accuracy; and (c) analysing Spanish political tweets to rank political leaders, parties and personalities for popularity. Sentiment in Twitter for key politicians broadly reflects the main official polls for popularity but not for voting intention. In addition, the data suggests that the primary role of Twitter in politics is to select and amplify political events published by traditional media. | es_ES |
dc.description.sponsorship | This research is partially supported by the Ministerio de Economía y Competitividad (FFI2014-51978-C2) and Xunta de Galicia (R2014/034). The first author is partially funded by the Ministerio de Educación, Cultura y Deporte (FPU13/01180) and Inditex-UDC 2014 grants for international visits. The authors thank the annotators for help with this research. | es_ES |
dc.description.sponsorship | Xunta de Galicia; R2014/034 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | SAGE Publications & CILIP | es_ES |
dc.relation | info:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FPU13%2F01180/ES/ | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FFI2014-51978-C2-1-R/ES/TECNOLOGIAS DE LA LENGUA PARA ANALISIS DE OPINIONES EN REDES SOCIALES | es_ES |
dc.relation.isversionof | https://doi.org/10.1177/01655515155989 | |
dc.relation.uri | https://doi.org/10.1177/01655515155989 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Popularity | es_ES |
dc.subject | Politics | es_ES |
dc.subject | Sentiment analysis | es_ES |
dc.subject | SentiStrength | es_ES |
dc.subject | es_ES | |
dc.title | The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweets | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Journal of Information Science | es_ES |
UDC.volume | 41 | es_ES |
UDC.issue | 6 | es_ES |
UDC.startPage | 799 | es_ES |
UDC.endPage | 813 | es_ES |
dc.identifier.doi | 10.1177/01655515155989 |
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