Lógica Fuzzy aplicada à análise comportamental e conhecimento da guerra cognitiva em redes sociais: um modelo de extração e mineração de dados

Abstract

The research aims to understand how behavior, emotion and subjectivity participate in the construction of a conflict or polarization of ideas as an instrument of Cognitive Warfare in social networks, between actors or groups of actors, for example on the Twitter and Facebook platform, through the application of computational methods or models that work on subjectivity between them, using algorithms based on machine learning. The sentiment of the actors' dialogues on the subject addressed in terms of the polarity of the content, classifying opinions, for example whether they are positive or neutral or negative, is also analyzed. We will use text mining and sentiment analysis techniques. The aim is to develop and present a text processing and analysis system that optimizes the identification of polarizing ideas and improves multi-criteria decision making within diverse contexts on social networks, taking into account feelings and emotions. The approach consists of identifying and collecting the opinions of Twitter users on certain subjects, in the effervescence of events surrounding the issues listed. Text mining and sentiment analysis techniques are applied to extract qualifiers from the data analyzed. In addition, we developed a data visualization system that relies on the parameterization of value ranges for colors. Our data suggests what is already known in the light of psycholinguistics: when humans express themselves, they can reveal a variety of emotions that they experience internally and that inspire their subjective experience, their actions and their communication.