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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.

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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.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 The Authors
Keywords: children protection; online grooming; behavioural patterns
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 41394
Depositing User: Miriam Fernandez
Date Deposited: 25 Nov 2014 12:53
Last Modified: 20 Dec 2017 16:53
URI: http://oro.open.ac.uk/id/eprint/41394
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