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Cano Basave, Amparo; Fernández, Miriam and Alani, Harith
(2014).
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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About
- Item ORO ID
- 41394
- Item Type
- Conference or Workshop Item
- ISBN
- 3-319-15168-1, 978-3-319-15168-7
- Keywords
- children protection; online grooming; behavioural patterns
- Academic Unit or 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)
- Copyright Holders
- © 2014 The Authors
- Depositing User
- Miriam Fernandez