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Fernández Crespo, M. (2013) Predicción electoral mediante análisis de redes sociales. Ph.D. Dissertation, Universidad Complutense de Madrid, Madrid.

has been cited by the following article:

  • TITLE: The Weighting Factors to Improve Predictability on Twitter

    AUTHORS: Jorge Arroba Rimassa, Rafael Muñoz Guillena, Fernando Llopis

    KEYWORDS: Twitter, Weighting Factors, Formalization of Social Networks

    JOURNAL NAME: Technology and Investment, Vol.9 No.1, February 27, 2018

    ABSTRACT: The result of the analysis of a thematic in a social network is to find a measure that allows the principal actors to know their performance, that is, they can define or maintain strategies and courses of action in order to optimize their communication. It is necessary to formally define the principles of analysis in Social Networks in order to use their characteristics better and to be able to contextualize the concept and use of weighting factors to improve their predictability. When Social Networks are going to be used as a mechanism to predict social behavior, for example, to predict the outcome of a political election, weighting factors must be introduced to try to match the data collected from the Social Network with those of a sample. In this article we have defined the methodology to incorporate the geographic weighting factors and several formulas have been created that allow reprocessing the data downloaded from Twitter in which its polarity has been determined by classical NLP methods to increase the predictive power.