Classification, identification, and analysis of events on twitter through data mining

dc.creatorSilva, Jesús
dc.creatorHiga, Yuki
dc.creatorCera Visbal, Juan Manuel
dc.creatorCabrera, Danelys
dc.creatorSenior Naveda, Alexa
dc.creatorFlores, Yasmin
dc.creatorPineda Lezama, Omar Bonerge
dc.date2021-01-15T18:12:41Z
dc.date2021-01-15T18:12:41Z
dc.date2021
dc.date.accessioned2023-10-03T20:07:42Z
dc.date.available2023-10-03T20:07:42Z
dc.identifierhttps://hdl.handle.net/11323/7699
dc.identifierhttps://doi.org/10.1007/978-981-15-7234-0_89
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9174400
dc.descriptionDue to its popularity, Twitter is currently one of the major players in the global network, which has established a new form of communication: the microblogging. Twitter has become an essential media network for the follow-up, diffusion and coordination of events of diverse nature and importance (Gonzalez-Agirre et al. in Multilingual central repository version 3.0. Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC’12). Istanbul, Turkey, 2012, [1]), such as a presidential campaign, a disaster situation, a war or the repercussion of information. In such scenario, it is considered a relevant source of information to know the opinions that are emitted about different issues or people. This research proposes the evaluation of several supervised classification algorithms to address the problem of opinion mining on Twitter.
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languagespa
dc.publisherCorporación Universidad de la Costa
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dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourceAdvances in Intelligent Systems and Computing
dc.sourcehttps://link.springer.com/chapter/10.1007/978-981-15-7234-0_89
dc.subjectMachine learning
dc.subjectTwitter
dc.subjectOpinion mining
dc.subjectClassification
dc.titleClassification, identification, and analysis of events on twitter through data mining
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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