An ANEW based Fuzzy Sentiment Analysis Model
Andrés Montoro-Montarroso, José Á. Olivas, Arturo Peralta, Francisco P. Romero, Jesus Serrano‐Guerrero · 2018
Within the framework of the Intelligent Data Suite (IDS) that is being developed by the company Prometeus Global Solutions, there is a Sentiment Analysis and Opinion Mining module focused on detecting `dangerous' (to the tool user company) messages on Social Media. This can be useful for sending `early warnings' to alert tool user company analysts to take preventive measures against potentially harmful messages. In this paper, a brief description of IDS features, regarding tweets filtering and classification is firstly presented. Affective Norms for English Words (ANEW) provides a set of normative emotional ratings for a large number of words in English and three emotions (valence, arousal and dominance) measures for each term. It is used as a basis for describing a fuzzy model containing five categories for representing the opinion of a microblogging text (very negative, negative, neutral, positive and very positive). The proposal is implemented and tested on the IDS framework.