An analysis of violence against women based on victims' reports - Corrêa, Isabella Tannús; Faria, Elaine Ribeiro (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI), 2021)
Every two seconds, a woman is a victim of physical or verbal violence in Brazil, and every 1.4 seconds, a woman is a victim of harassment. Due to the growth of anthropology and notions of feminism, violence against women has been seen as a public problem. This work proposes a method to analyse reports of violence against women using text mining techniques to characterize the aggression or the aggressor. We collected data from electronic newspapers, sites, and social networks, pre-processed them, extracted topics from the data using the Latent Dirichlet Allocation (LDA), and classified the text according to the frequency of occurrence (constant or sporadic) using the Naive Bayes algorithm. Among the analyzed cases, most of them indicate that the violence was sporadic; it happened once. The results suggest that most reports of constant violence – meaning that they occur frequently – are related to someone close to the victim, such as a family member, spouse or friend. Words such as ”speak”, ”say” and ”report” are frequent, indicating the victim’s willingness to express the aggression. When categorizing documents into topics, it is possible to find scenarios of family abuse executed by the father or a brother, and also the presence of sexual violence as one of the aggressions suffered.