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Respond2Hate aims to empower users to filter hate speech from their social media feeds using a browser extension. By leveraging adaptive machine learning techniques, the project seeks to create a localized solution for hate speech detection in diverse cultural contexts.
Hate speech is a worldwide phenomenon that is increasingly pervading online spaces, creating an unsafe environment for users.
While tech companies address this problem by server-side filtering using machine learning models trained on large datasets, these automatic methods cannot be applied to most languages due to lack of available training data.Based on recent results of the PI's ERC project on multilingual representation models in low-resource settings, Respond2Hate aims at developing a pilot…
LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
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