Drury, B. M. and Morais Drury, S and Md Arafatur, Rahman and Ullah, Ihsan (2022) A Social Network of Crime: A Review of The Use of Social Networks for Crime and The Detection of Crime. Online Social Networks and Media. ISSN 2468-6964 (Accepted for Publication)
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Text (A survey about the use of AI to commit and detect crime on social media)
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Abstract
Social media is used to commit and detect crimes. With automated methods, it is possible to scale both crime and detection of crime to a large number of people. The ability of criminals to reach large numbers of people has made this area subject to frequent study, and consequently, there have been several surveys that have reviewed specific crimes committed on social platforms. Until now, there has not been a review article that considers all types of crimes on social media, their similarity as well as their detection. The demonstration of similarity between crimes and their detection methods allows for the transfer of techniques and data between domains. This survey, therefore, seeks to document the crimes that have been committed on social media, and demonstrate their similarity through a taxonomy of crimes. Also, this survey documents publicly available datasets. Finally, this survey provides suggestions for further research in this field.
| Item Type: | Article |
|---|---|
| Additional Information and Comments: | “NOTICE: this is the author’s version of a work that was accepted for publication in Online Social Networks and Media. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. |
| Keywords: | Social Media, Cybercrime, Machine Learning, Crime Prediction, NLP |
| Faculty / Department: | Faculty of Human and Digital Sciences > Mathematics and Computer Science |
| Depositing User: | Brett Drury |
| Date Deposited: | 10 May 2022 09:07 |
| Last Modified: | 30 Sep 2024 00:15 |
| URI: | https://hira.hope.ac.uk/id/eprint/3537 |
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