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, pp. 412–427.

DOI: https://doi.org/10.1007/978-3-319-13734-6_30

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.

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