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Abstract
This paper describes a machine learning approach to detect
sexually predatory behaviour in the massively multiplayer online game for children, MovieStarPlanet. The goal of this work is to take a chat log as an input and outputs its label as either the predatory category or the non-predatory category. From the raw in-game chat logs provided by MovieStarPlanet, we first prepared three sub datasets via extensive preprocessing. Then, two machine learning algorithms, naive Bayes and Decision Tree, were employed to model the predatory behaviour using different feature sets. Our evaluation has revealed that the proposed
approach achieved high accuracies in detecting predatory chats
sexually predatory behaviour in the massively multiplayer online game for children, MovieStarPlanet. The goal of this work is to take a chat log as an input and outputs its label as either the predatory category or the non-predatory category. From the raw in-game chat logs provided by MovieStarPlanet, we first prepared three sub datasets via extensive preprocessing. Then, two machine learning algorithms, naive Bayes and Decision Tree, were employed to model the predatory behaviour using different feature sets. Our evaluation has revealed that the proposed
approach achieved high accuracies in detecting predatory chats
Originalsprog | Engelsk |
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Publikationsdato | 9 nov. 2013 |
Antal sider | 11 |
Status | Udgivet - 9 nov. 2013 |
Begivenhed | The 2nd Workshop on Games and NLP: Workshop at the 6th International Conference on Interactive Digital Storytelling - Bahcesehir University Galata Campus (Animation Lab), Istanbul, Tyrkiet Varighed: 9 nov. 2013 → 9 nov. 2013 Konferencens nummer: 6 http://gamesandnarrative.net/icids2013/call-to-participate-in-workshops |
Workshop
Workshop | The 2nd Workshop on Games and NLP |
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Nummer | 6 |
Lokation | Bahcesehir University Galata Campus (Animation Lab) |
Land/Område | Tyrkiet |
By | Istanbul |
Periode | 09/11/2013 → 09/11/2013 |
Internetadresse |
Emneord
- NLP
- predator
- game
- text classification
Fingeraftryk
Dyk ned i forskningsemnerne om 'Detecting Predatory Behaviour in Online Game Chats'. Sammen danner de et unikt fingeraftryk.Projekter
- 1 Afsluttet
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SIREN: Social games for conflIct REsolution based on natural iNteraction
Yannakakis, G. (PI), Togelius, J. (CoI), Cheong, Y.-G. (CoI), Khaled, R. (CoI), Grappiolo, C. (CoI), Liapis, A. (CoI) & Holmgård, C. (CoI)
01/09/2010 → 31/08/2013
Projekter: Projekt › Forskning