Detecting child grooming behaviour patterns on social media

Cano Basave, Amparo; Fernández, Miriam and Alani, Harith (2014). Detecting child grooming behaviour patterns on social media. In: SociInfo 2014: The 6th International Conference on Social Informatics, 10-13 Nov 2014, Barcelona, Spain.

URL: https://www.springer.com/gp/book/9783319151670

Abstract

Online paedophile activity in social media has become a major concern in society as Internet access is easily available to a broader younger population. One common form of online child exploitation is child grooming, where adults and minors exchange sexual text and media via social media platforms. Such behaviour involves a number of stages performed by a predator (adult) with the final goal of approaching a victim (minor) in person. This paper presents a study of such online grooming stages from a machine learning perspective. We propose to characterise such stages by a series of features covering sentiment polarity, content, and psycho-linguistic and discourse patterns. Our experiments with online chatroom conversations show good results in automatically classifying chatlines into various grooming stages. Such a deeper understanding and tracking of predatory behaviour is vital for building robust systems for detecting grooming conversations and potential predators on social media.

Viewing alternatives

Download history

Item Actions

Export

About

Recommendations