Relevance as an enhancer of votes on Twitter

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/77753
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Title: Relevance as an enhancer of votes on Twitter
Authors: Arroba Rimassa, Jorge | Llopis, Fernando | Muñoz, Rafael
Research Group/s: Procesamiento del Lenguaje y Sistemas de Información (GPLSI)
Center, Department or Service: Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos
Keywords: Relevance | Twitter | Election process
Knowledge Area: Lenguajes y Sistemas Informáticos
Issue Date: 2018
Publisher: Editorial Universitat Politècnica de València
Citation: Arroba Rimassa, Jorge; Llopis, Fernando; Muñoz Guillena, Rafael. “Relevance as an enhancer of votes on Twitter”. En: Domenech, Josep; Vicente, María Rosalía; Blazquez, Desamparados (Eds.). CARMA 2018: 2nd International Conference on Advanced Research Methods and Analytics, July 12-13, 2018, Valencia, Spain. València: Editorial Universitat Politècnica de València, 2018. ISBN 978-84-9048-689-4, pp. 63-70
Abstract: The concept of the influence of Katz and Lazarfeld given in the last century has evolved thanks to the appearance of Social Networks and especially Twitter. Because this microblogging has allowed candidates for any election process to be closer to their electors and also allows an analysis of the contents of the messages to determine their polarity. The relevance of the messages that measure the level of influence that can be had in the voters, incorporated into the traditional analysis of the Social Networks allow to have a greater degree of precision in the electoral predictions that are made using natural language processing, NLP. We have introduced in the methodology that we propose a mechanism to enhance the votes of those messages that have a greater relevance and turn them into votes in order to improve the predictability of the electoral results. The proposed methodology was applied in the election for President of the Republic of Ecuador that was held on February 19, 2017, obtaining a Mean Average Error, MAE = 1.4 that demonstrates the relevance of incorporating the variable Relevance as an enhancer of votes.
Sponsor: This research work has been partially funded by the University of Alicante, Generalitat Valenciana , Spanish Government, Ministerio de Educación, Cultura y Deporte and ASAP - Ayudas Fundación BBVA a equipos de investigación científica 2016 (FUNDACIONBBVA2-16PREMIO) through the projects, TIN2015-65100-R, TIN2015-65136-C2-2-R, PROMETEOII/2014/001, GRE16- 01: “Plataforma inteligente para recuperación, análisis y representación de la información generada por usuarios en Internet” and “Análisis de Sentimientos Aplicado a la Prevención del Suicidio en las Redes Sociales” (PR16_SOC_0013).
URI: http://hdl.handle.net/10045/77753
ISBN: 978-84-9048-689-4
DOI: 10.4995/CARMA2018.2018.8311
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Rights: This work is licensed under a Creative Commons License CC BY-NC-ND 4.0
Peer Review: si
Publisher version: https://doi.org/10.4995/CARMA2018.2018.8311
Appears in Collections:INV - GPLSI - Comunicaciones a Congresos, Conferencias, etc.

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