The Open UniversitySkip to content

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.

Full text available as:
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (393kB) | Preview
Google Scholar: Look up in Google Scholar


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: 31 May 2019 21:05
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU