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dc.creatorSilva, Jesús
dc.creatorCera Visbal, Juan Manuel
dc.creatorVargas, Jesús
dc.creatorPineda, Omar
dc.date.accessioned2020-11-12T21:15:34Z
dc.date.available2020-11-12T21:15:34Z
dc.date.issued2020
dc.identifier.issn21945357
dc.identifier.urihttps://hdl.handle.net/11323/7295
dc.description.abstractThis paper presents a series of experiments aimed at the sentiment analysis on texts posted in Twitter. In particular, several morphological characteristics are studied for the representation of texts in order to determine those that provide the best performance when detecting the emotional charge contained in the Tweets.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherCorporación Universidad de la Costaspa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceAdvances in Intelligent Systems and Computingspa
dc.subjectMorphological characteristicsspa
dc.subjectSentiment analysisspa
dc.subjectTwitterspa
dc.subjectWekaspa
dc.titleSentiment analysis in twitter: Impact of morphological characteristicsspa
dc.typePreprintspa
dcterms.referencesZahra, K., Imran, M., Ostermann, F.O.: Automatic identification of eyewitness messages on Twitter during disasters. Inf. Process. Manag. 57(1), 102107 (2020)spa
dcterms.referencesKaul, A., Mittal, V., Chaudhary, M., Arora, A.: Persona classification of celebrity Twitter users. In: Digital and Social Media Marketing, pp. 109–125. Springer, Cham (2020)spa
dcterms.referencesMotamedi, R., Jamshidi, S., Rejaie, R., Willinger, W.: Examining the evolution of the Twitter elite network. Soc. Netw. Anal. Mining 10(1), 1 (2020)spa
dcterms.referencesRodríguez-Ruiz, J., Mata-Sánchez, J.I., Monroy, R., Loyola-González, O., López-Cuevas, A.: A one-class classification approach for bot detection on Twitter. Comput. Secur. 91, 101715 (2020)spa
dcterms.referencesVásquez, C., Torres-Samuel, M., Viloria, A., Borrero, T.C., Varela, N., Lis-Gutiérrez, J.P., Gaitán-Angulo, M.: Visibility of research in universities: the triad product-researcher-institution. Case: Latin american countries. In: International Conference on Data Mining and Big Data, pp. 225–234. Springer, Cham, June 2018spa
dcterms.referencesBurnap, P., Williams, M.L.: Us and them: identifying cyber hate on Twitter across multiple protected characteristics. EPJ Data Sci. 5(1), 11 (2016)spa
dcterms.referencesLuo, F., Cao, G., Mulligan, K., Li, X.: Explore spatiotemporal and demographic characteristics of human mobility via Twitter: a case study of Chicago. Appl. Geogr. 70, 11–25 (2016)spa
dcterms.referencesKabakuş, A.T., Şimşek, M.: An analysis of the characteristics of verified Twitter users. Sakarya Univ. J. Comput. Inf. Sci. 2(3), 180–186 (2019)spa
dcterms.referencesNguyen, Q.C., Brunisholz, K.D., Yu, W., McCullough, M., Hanson, H.A., Litchman, M.L., Li, F., Wan, Y., VanDerslice, J.A., Wen, M., Smith, K.R.: Twitter-derived neighborhood characteristics associated with obesity and diabetes. Sci. Rep. 7(1), 1–10 (2017)spa
dcterms.referencesGurajala, S., White, J.S., Hudson, B., Voter, B.R., Matthews, J.N.: Profile characteristics of fake Twitter accounts. Big Data Soc. 3(2), 2053951716674236 (2016)spa
dcterms.referencesChu, K.H., Majmundar, A., Allem, J.P., Soto, D.W., Cruz, T.B., Unger, J.B.: Tobacco use behaviors, attitudes, and demographic characteristics of tobacco opinion leaders and their followers: Twitter analysis. J. Med. Internet Res. 21(6), e12676 (2019)spa
dcterms.referencesAgarwal, A., Toshniwal, D.: Face off: travel habits, road conditions and traffic city characteristics bared using Twitter. IEEE Access 7, 66536–66552 (2019)spa
dcterms.referencesKim, Y.H., Woo, H.J.: Exploring Spatiotemporal Characteristics of Twitter data Using Topic Modelling Techniques. Abstracts of the ICA, 1 (2019)spa
dcterms.referencesJamison, A.M., Broniatowski, D.A., Quinn, S.C.: Malicious actors on Twitter: a guide for public health researchers. Am. J. Public Health 109(5), 688–692 (2019)spa
dcterms.referencesTorres-Samuel, M., Vásquez, C., Viloria, A., Lis-Gutiérrez, J.P., Borrero, T.C., Varela, N.: Web visibility profiles of top100 Latin American universities. In: International Conference on Data Mining and Big Data, pp. 254–262. Springer, Cham, June 2018spa
dcterms.referencesSaeidi, M., Venerandi, A., Capra, L., Riedel, S.: Community Question Answering Platforms vs. Twitter for Predicting Characteristics of Urban Neighbourhoods. arXiv preprint arXiv:1701.04653 (2017)spa
dcterms.referencesSilva, J., Varela, N., Ovallos-Gazabon, D., Palma, H.H., Cazallo-Antunez, A., Bilbao, O.R., Llinás, N.O., Lezama, O.B.P.: Data mining and social network analysis on Twitter. In: International Conference on Communication, Computing and Electronics Systems, pp. 401–408. Springer, Singapore (2020)spa
dcterms.referencesSilva, J., Naveda, A.S., Suarez, R.G., Palma, H.H., Núñez, W.N.: Method for collecting relevant topics from Twitter supported by big data. In: Journal of Physics: Conference Series, vol. 1432, no. 1, p. 012094. IOP Publishing, January 2020spa
dc.type.hasVersioninfo:eu-repo/semantics/draftspa
dc.source.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85089715269&doi=10.1007%2f978-3-030-53036-5_29&partnerID=40&md5=f59d26e93a8bd64ecb876d07f838daabspa
dc.rights.accessrightsinfo:eu-repo/semantics/closedAccessspa
dc.date.embargoEnd2021-06-19


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