Toxicity Detection in Multiplayer Online Games
M. Märtens (TU Delft - Network Architectures and Services)
S Shen (Parallel and Distributed Processing Laboratory)
Alexandru Iosup (TU Delft - Data-Intensive Systems)
F.A. Kuipers (TU Delft - Network Architectures and Services)
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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.