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SUMMARY:Masterarbeit im Studiengang Informatik von Nadja Bauer: Acceptance of AI-Based Hate Speech Moderation on Social Media: The Impact of Familiarity with AI Systems\, IT Knowledge\, and Social Media Use
DESCRIPTION:As the prevalence of hate speech on social media continues to rise\, there is an increasing rationale for the implementation of AI-based moderation systems. This study addresses the existing research gap in understanding how individual factors\, including user familiarity with AI\, IT proficiency\, and social media use influence attitudes towards AI-based hate speech moderation. Based on an extensive literature review\, the study develops three hypotheses: General familiarity with AI systems negatively correlates with acceptance of AI-based hate speech moderation (H1); higher levels of IT knowledge positively correlate with acceptance of AI-based hate speech moderation (H2); and a greater extent of social media use is positively associated with acceptance of AI-based moderation (H3). To explore these hypotheses\, an online survey on the use of AI to address hate speech on social media is conducted (N = 115)\, and the data is analyzed using a multiple linear regression model. The results show that familiarity with AI systems does not significantly influence acceptance\, while frequent social media use shows a slight\, non-significant positive trend toward acceptance. In contrast\, a notable negative correlation was found between IT knowledge and the acceptance of AI-based hate speech moderation. These findings provide both theoretical insights and practical implications for the use of AI-based content moderation systems on social media. \nBetreuer: Julian Bäumler\, M.A.\nPrüfer: Prof. Dr. Dr. Christian Reuter
URL:https://peasec.de/event/masterarbeit-im-studiengang-informatik-von-nadja-bauer-acceptance-of-ai-based-hate-speech-moderation-on-social-media-the-impact-of-familiarity-with-ai-systems-it-knowledge-and-social-media-use/
LOCATION:Zoom
CATEGORIES:Kolloquium
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