Shane Murnion
Machine learning and semantic analysis of in-game chat for cyber bullying
Murnion, Shane; Buchanan, William J.; Smales, Adrian; Russell, Gordon
Authors
Prof Bill Buchanan B.Buchanan@napier.ac.uk
Professor
Adrian Smales
Dr Gordon Russell G.Russell@napier.ac.uk
Associate Professor
Abstract
One major problem with cyberbullying research is the lack of data, since researchers are traditionally forced to rely on survey data where victims and perpetrators self-report their impressions. In this paper, an automatic data collection system is presented that continuously collects in-game chat data from one of the most popular online multi-player games: World of Tanks. The data was collected and combined with other information about the players from available online data services. It presents a scoring scheme to enable identification of cyberbullying based on current research. Classification of the collected data was carried out using simple feature detection with SQL database queries and compared to classification from AI-based sentiment text analysis services that have recently become available and further against manually classified data using a custom-built classificationclient built for this paper. The simple SQL classification proved to be quite useful at identifying some features of toxic chat such as the use of bad language or racist sentiments, however the classification by the more sophisticated online sentiment analysis services proved to be disappointing. The results were then examined for insights into cyberbullying within this game and it was shown that it should be possible to reduce cyberbullying within the World of Tanks game by a significant factor by simply freezing the player’s ability to communicate through the in-game chat function for a short period after the player is killed within a match. It was also shown that very new players are much less likely to engage in cyberbullying, suggesting that it may be a learned behaviour from other players.
Citation
Murnion, S., Buchanan, W. J., Smales, A., & Russell, G. (2018). Machine learning and semantic analysis of in-game chat for cyber bullying. Computers and Security, 76, 197-213. https://doi.org/10.1016/j.cose.2018.02.016
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 23, 2018 |
Online Publication Date | Mar 9, 2018 |
Publication Date | 2018-07 |
Deposit Date | Mar 11, 2018 |
Publicly Available Date | Mar 10, 2019 |
Journal | Computers & Security |
Print ISSN | 0167-4048 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 76 |
Pages | 197-213 |
DOI | https://doi.org/10.1016/j.cose.2018.02.016 |
Keywords | Cyberbullying, machine learning, on-line gaming, multiplayer games, sentiment analysis, |
Public URL | http://researchrepository.napier.ac.uk/Output/1111954 |
Contract Date | Mar 11, 2018 |
Files
Machine learning and semantic analysis of in-game chat for cyber-bullying
(1 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Securing IoT: Mitigating Sybil Flood Attacks with Bloom Filters and Hash Chains
(2024)
Journal Article
An omnidirectional approach to touch-based continuous authentication
(2023)
Journal Article
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search