Toxicity Detection in Multiplayer Online Games

Conference paper (2015)

Authors

M. Märtens Network Architectures and Services - EEMCS
S. Shen Parallel and Distributed Processing Laboratory
A. Iosup Data-Intensive Systems - EEMCS
F.A. Kuipers Network Architectures and Services - EEMCS
Research Group
Network Architectures and Services (EEMCS) (TU Delft)
Copyright: © 2015 M. Märtens, S. Shen, A. Iosup, F.A. Kuipers
DOI: https://doi.org/10.1109/NetGames.2015.7382991
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Published Date

2015

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Quantum & Computer Engineering

Research Group

Network Architectures and Services

Abstract

Social interactions in multiplayer online games are an essential feature for a growing number of players world-wide. However, this interaction between the players might lead to the emergence of undesired and unintended behavior, particularly if the game is designed to be highly competitive. Communication channels might be abused to harass and verbally assault other players, which negates the very purpose of entertainment games by creating a toxic player-community. By using a novel natural language processing framework, we detect profanity in chat-logs of a popular Multiplayer Online Battle Arena (MOBA) game and develop a method to classify toxic remarks. We show how toxicity is non-trivially linked to game success.

Files

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