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  4. 2.01 Detecting grooming behaviour on social media

2.01 Detecting grooming behaviour on social media

Academic team: Prof Harith Alani, Dr Elizabeth Cano, Dr Miriam Fernandez,  
Policing partners: Dorset Police, Avon and Somerset Police, Lancashire Constabulary
Status: Complete

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Online paedophile activity has become a major concern in society with the internet widely available to the general population and young people.

This piece of research looked into whether the different stages of online grooming behaviour could be automatically detected. The proposed approach combines Machine Learning (ML) techniques  with existing psychological theories and discourse studies to better encapsulate existing knowledge of online grooming. 

The results of this study demonstrate the effectiveness of this approach for the automatic detection of online grooming stages, opening new possibilities for addressing predator grooming behaviour online, and helping policing organisations to act in a preventive way.

Outputs

Title Outputs type Lead academic Year
Detecting child grooming behaviour patterns on social media Executive summary Alani, H 2017
Detecting grooming behaviour on social media Presentation Alani, H 2017
Detecting child grooming behaviour patterns on social media Final report Alani, H 2016

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