Exploring Automatic Identification of Fantasy-Driven and Contact-Driven Sexual Solicitors

Abstract

In an increasingly computer-mediated world, it is easier to start conversations with people online, making it convenient to build trust with people based on their online persona. This encourages people with malevolent intentions to take advantage of trustful youngsters by means of various internet-based messaging platforms and subsequently inflicting harm to people below the legal age if a physical meeting is arranged. While previous research has prioritized the automatic identification of online solicitors by means of analyzing online chat conversations, little work has been done in terms of studying the conversational features of chats involving fantasy-driven and contact-driven online solicitors. This study focuses on 271 conversations extracted from Perverted-Justice, an online repository of chats between a predator and a volunteer pretending to be underage and presents results from training a model to triage between fantasy and contact-driven online solicitors.

Publication
In 2019 IEEE International Conference on Robotic Computing (IRC)
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Kanishka Misra
Kanishka Misra
PhD Student

My research interests include Natural Language Processing, Cognitive Science, and Deep Learning. matter.

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