Toward Spotting the Pedophile Telling victim from predator in text chats

This paper presents the results of a pilot study on using automatic text categorization techniques in identifying online sexual predators. We report on our SVM and k-NN models. Our distance weighted k-NN classifier reaches an f-measure of 0.943 on test data distinguishing the child and the victim sides of text chats between sexual predators and volunteers posing as underage victims.

• Type: Conference
• Year: 2007
• Where: SEMCO
• Authors: Nick Pendar
• Keywords: Automatic Text Categorization, Online Sexual Predators, Semantic Computing, SEMCO 2007, Sexual Predators