Paper Title
Detecting Tamil Textual Threats in Social Media Using Artificial Intelligence
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Abstract
In recent decades, the proliferation of social networks has facilitated extensive communication among individuals globally through microblogging technologies. This has enabled the free exchange of ideas, feelings, and information on a massive scale and in real-time. However, this increased connectivity has also led to the proliferation of offensive language, including hate speech and cyberbullying, on social media platforms. Legislation in various countries seeks to address this issue, with measures such as Germany's Network Enforcement Act. Advanced technical approaches are being developed to assist social media platforms in enforcing these laws, including the detection of offensive language using artificial intelligence (AI) techniques. While offensive language detection has been explored in various languages, including English, German, Turkish, Hindi, Chinese, and Arabic, addressing this issue in Tamil poses its own challenges due to linguistic complexities and dialectical variations. This paper aims to explore the implemented AI approaches, performance measurement methodologies, and dataset details for offensive language detection in Tamil. By providing a comprehensive overview of existing research, this paper aims to guide future studies and facilitate a more unified approach to addressing the issue of offensive language in Tamil social media.
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How To Cite (APA)
ABISHEK A & Thadeus Cruz Govindapillai (March-2024). Detecting Tamil Textual Threats in Social Media Using Artificial Intelligence. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), d282-d286. https://ijnrd.org/papers/IJNRD2403338.pdf
Issue
Volume 9 Issue 3, March-2024
Pages : d282-d286
Other Publication Details
Paper Reg. ID: IJNRD_215939
Published Paper Id: IJNRD2403338
Downloads: 000122257
Research Area: Engineering
Author Type: Indian Author
Country: DHARMAPURI, Tamilnadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403338.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403338
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