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Enabling Informational Autonomy through Explanation of Content Moderation: UI Design for Hate Speech Detection

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dc.contributor.authorSontheimer, Lukas
dc.contributor.authorSchäfer, Johannes
dc.contributor.authorMandl, Thomas
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.description.abstractContent moderation using AI and in particular Hate Speech detection has been a research topic with a focus on natural language processing, classification algorithms and data benchmarks. Less attention has been dedicated to how the classification systems are later integrated into tools which support users in an application task. In this paper we review existing tools and prototypes. Furthermore, we design and implement an online user interface for explainability. The system is connected to a neural network classifier based on the HASOC benchmark. The interface allows users to enter messages, observe classification decisions and see similar messages for explanation. It provides support for users of social media who are interested in the performance of AI systems for content moderation and who want to observe the performance of hate speech detection tools. A qualitative evaluation with experts showed that our system can be helpful to bridge the gap between humans and AI.en
dc.identifier.doi10.18420/muc2022-mci-ws12-260
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39101
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2022 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.titleEnabling Informational Autonomy through Explanation of Content Moderation: UI Design for Hate Speech Detectionen
dc.typeText/Workshop Paper
gi.citation.publisherPlaceBonn
gi.conference.date4.-7. September 2022
gi.conference.locationDarmstadt
gi.conference.sessiontitleMCI-WS12: UCAI 2022: Workshop on User-Centered Artificial Intelligence
gi.document.qualitydigidoc

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