Automatic Polarity Classifier Model of Opinionso about Prostate Cancer on Facebook®

Abstract

Disease prevention campaigns, especially those carried out on the Internet, are of paramount importance today because, through them, it is possible to understand, in realtime, at least partially, if the population is well receiving the campaign [1]. This context requires automatic monitoring, which works as an auxiliary tool for managers in decision-making processes. The mission of extracting useful information from unstructured databases (text, speech, etc.), as in social networks, is still a significant challenge. Many researchers in the Natural Language Processing (PLN) subfield have sought the solution to this question called sentiment or opinion analysis [2,3,5]. Therefore, the purpose of this study is to develop and analyze an automatic opinion polarity classifier model applied to the postings on prostate cancer on the Facebook page named November Blue in 2018.