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Juan Manuel Pérez Trujillo ; Romario Albeiro Sánchez Montero ;Sistemas & Telemática 2016, 14 39

Autor: Sonia Ordoñez Salinas

Fuente: http://www.redalyc.org/articulo.oa?id=411549534003


Introducción



Sistemas & Telemática ISSN: 1692-5238 EditorSyT@icesi.edu.co Universidad ICESI Colombia Ordoñez Salinas, Sonia; Pérez Trujillo, Juan Manuel; Sánchez Montero, Romario Albeiro Election analysis in Colombia and Venezuela 2015 through sentiment analysis and Twitter Sistemas & Telemática, vol.
14, núm.
39, 2016, pp.
57-70 Universidad ICESI Cali, Colombia Available in: http:--www.redalyc.org-articulo.oa?id=411549534003 How to cite Complete issue More information about this article Journals homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative Ordoñez, S., Pérez, J.
M., & Sánchez, R.
(2016).
Election analysis in Colombia and Venezuela 2015 through sentiment analysis and Twitter.
Sistemas & Telemática, 14(39), 57-70.
doi:10.18046-syt.v14i39.2349 Discussion paper - Artículo de reflexión - Documento de discussão - Tipo 2 Election analysis in Colombia and Venezuela 2015 through sentiment analysis and Twitter Sonia Ordoñez Salinas, Ph.D - sordonez@udistrital.edu.co Juan Manuel Pérez Trujillo - jmperezt@correo.udistrital.edu.co Romario Albeiro Sánchez Montero - rasanchezm@correo.udistrital.edu.co Grupo de investigación Gesdatos Universidad Distrital Francisco José de Caldas, Bogotá-Colombia ABSTRACT This paper presents an analysis of the accounts of the main candidates in the regional elections on October 25, 2015 in Colombia (Bogotá, Medellin and Cali) and the official hashtags of the two main parties for parliamentary elections on December 6, 2015 in Venezuela (PSUV and MUD) in order to determine the positive or negative trends and compare them with the results of the respective elections.
To develop the analysis, we resorted to the technique of sentiment analysis own of data mining and the use of descriptive statistics, concluding that sentiment analysis for estimating trends requires process...





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