Detecting child grooming behaviour patterns on social media
- Submitting institution
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The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1587365
- Type
- E - Conference contribution
- DOI
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10.1007/978-3-319-13734-6_30
- Title of conference / published proceedings
- SociInfo 2014: The 6th International Conference on Social Informatics
- First page
- 412
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- November
- Year of publication
- 2014
- URL
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https://www.springer.com/gp/book/9783319151670
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
-
-
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Paper was first to incorporate grooming models from psychology in the design of machine learning methods to automatically identify grooming behaviour. It is often cited for moving away from binary detection and focusing instead on detecting different stages of grooming which is more valuable for early detection of such offences (Escalante et al. 2017, Al-Khateeb et al, 2016). Work was presented on a panel organised by the National Society for the Prevention of Cruelty to Children, and formed the basis for another project with the Met and NSPCC to protect children (Strategy and Governance, Metropolitan Police Service, details on request).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -