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Caste-based hate speech moderation on Facebook (Meta) and Twitter (X)
Abstract
The paper will investigate the complexities involved in moderating casteist content on major social media platforms. Focusing on the challenges of categorizing hate speech targeting India's marginalized caste-oppressed minorities, the research aims to delve into the mechanisms utilized by platforms for content moderation. It will critically analyze existing categorization systems, exploring the efficacy and limitations in identifying and addressing casteist comments. By leveraging information sciences concepts like grounded coding and taxonomies, the study will elucidate the complexities of classifying caste-related hate speech within these systems. Moreover, it will highlight the implications of inadequate categorization on content visibility and community impact.
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