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.