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dc.contributor.authorFrommel, Julian
dc.contributor.authorMandryk, Regan
dc.contributor.editorMarky, Karola
dc.contributor.editorGrünefeld, Uwe
dc.contributor.editorKosch, Thomas
dc.date.accessioned2022-08-30T10:27:43Z
dc.date.available2022-08-30T10:27:43Z
dc.date.issued2022
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/39102
dc.description.abstractToxicity 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.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2022 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.subjecttoxicity
dc.subjectreporting
dc.subjectprediction
dc.subjectclassification
dc.subjectmultiplayer
dc.subjectesports
dc.subjectcompetitive
dc.subjectgame
dc.subjectgaming
dc.titleEffective Toxicity Prediction in Online Multiplayer Gaming: Four Obstacles to Making Approaches Usableen
dc.typeText/Conference Poster
dc.pubPlaceBonn
mci.document.qualitydigidoc
mci.conference.sessiontitleMCI-WS12: UCAI 2022: Workshop on User-Centered Artificial Intelligence
mci.conference.locationDarmstadt
mci.conference.date4.-7. September 2022
dc.identifier.doi10.18420/muc2022-mci-ws12-315


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