A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages

November 28, 2024 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages"

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Authors Susmita Das, Arpita Dutta, Kingshuk Roy, Abir Mondal, Arnab Mukhopadhyay arXiv ID 2411.19017 Category cs.CL: Computation & Language Cross-listed cs.LG Citations 5 Venue arXiv.org Last Checked 3 days ago
Abstract
The expanding influence of social media platforms over the past decade has impacted the way people communicate. The level of obscurity provided by social media and easy accessibility of the internet has facilitated the spread of hate speech. The terms and expressions related to hate speech gets updated with changing times which poses an obstacle to policy-makers and researchers in case of hate speech identification. With growing number of individuals using their native languages to communicate with each other, hate speech in these low-resource languages are also growing. Although, there is awareness about the English-related approaches, much attention have not been provided to these low-resource languages due to lack of datasets and online available data. This article provides a detailed survey of hate speech detection in low-resource languages around the world with details of available datasets, features utilized and techniques used. This survey further discusses the prevailing surveys, overlapping concepts related to hate speech, research challenges and opportunities.
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