DocumentCode
3466394
Title
Toward Spotting the Pedophile Telling victim from predator in text chats
Author
Pendar, Nick
Author_Institution
Iowa State Univ., Ames
fYear
2007
fDate
17-19 Sept. 2007
Firstpage
235
Lastpage
241
Abstract
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.
Keywords
Internet; pattern classification; support vector machines; text analysis; Internet; automatic text categorization technique; online sexual predators; pedophile telling victim spotting; support vector machines; text chats; weighted k-NN classifier model; Application software; Data acquisition; Human computer interaction; Internet; Law enforcement; Support vector machine classification; Support vector machines; Testing; Text categorization; World Wide Web;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing, 2007. ICSC 2007. International Conference on
Conference_Location
Irvine, CA
Print_ISBN
978-0-7695-2997-4
Type
conf
DOI
10.1109/ICSC.2007.32
Filename
4338354
Link To Document