Identification of Brazilian sexual predators through analysis of Internet chats

• Leonardo Ferreira dos Santos CEFET-RJ
• Gustavo Paiva Guedes CEFET-RJ

DOI: https://doi.org/10.5753/brasnam.2019.6556

Abstract

Nowadays, social applications represent one of the main threats to children and adolescents on the Internet. Among the various existent risks is the presence of sexual predators that seek, among the most diverse purposes, to obtain child pornographic content, to extort for financial purposes and, in more severe scenarios, the sexual abuse. The present work aims to identify Brazilian sexual predators through Convolutional Neural Networks. In order to achieve this goal, it is considered conversations coming from criminal evidence that recently became publicly available. Preliminary results consolidate the presented methodology as an alternative for tasks of binary classification of texts for the Portuguese language.

Keywords: Data Mining, Text Classification, PAN-2012, Sexual Predator Identification, Machine Learning, Convolutional Neural Networks, Social Networks, Chat Logs

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