Effective Toxicity Prediction in Online Multiplayer Gaming: Four Obstacles to Making Approaches Usable
dc.contributor.author | Frommel, Julian | |
dc.contributor.author | Mandryk, Regan | |
dc.contributor.editor | Marky, Karola | |
dc.contributor.editor | Grünefeld, Uwe | |
dc.contributor.editor | Kosch, Thomas | |
dc.date.accessioned | 2022-08-30T10:27:43Z | |
dc.date.available | 2022-08-30T10:27:43Z | |
dc.date.issued | 2022 | |
dc.description.abstract | Toxicity represents a threat to the safety and health of online multiplayer gaming communities. This has been recognized by industry, academia, and players and led to efforts for combating toxicity, including different approaches for predicting toxicity from behaviour. Despite promising results, such approaches have not yet been able to meaningfully combat toxicity at scale. In this position paper, we describe four obstacles that impede usable applied toxicity prediction in multiplayer games that could help to combat harm.We want to foster a discussion about how user-centered artificial intelligence approaches may help solve these obstacles. | en |
dc.identifier.doi | 10.18420/muc2022-mci-ws12-315 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/39102 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | Mensch und Computer 2022 - Workshopband | |
dc.relation.ispartofseries | Mensch und Computer | |
dc.subject | toxicity | |
dc.subject | reporting | |
dc.subject | prediction | |
dc.subject | classification | |
dc.subject | multiplayer | |
dc.subject | esports | |
dc.subject | competitive | |
dc.subject | game | |
dc.subject | gaming | |
dc.title | Effective Toxicity Prediction in Online Multiplayer Gaming: Four Obstacles to Making Approaches Usable | en |
dc.type | Text/Workshop Paper | |
gi.citation.publisherPlace | Bonn | |
gi.conference.date | 4.-7. September 2022 | |
gi.conference.location | Darmstadt | |
gi.conference.sessiontitle | MCI-WS12: UCAI 2022: Workshop on User-Centered Artificial Intelligence | |
gi.document.quality | digidoc |
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