A Practical Approach to Detect Hateful and Nonhateful Language
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Abstract
Hate speech is a big problem in today’s online world due to the rise of social media and internet communities. Researchers are coming up with novel approaches to recognize and suppress hate speech using language processing tools. Hate speech has the potential to incite violence and prejudice in the real world as well as create a negative online atmosphere among communities. Owing to the massive amount of data, automated systems employing NLP techniques are essential in recognizing and removing this type of information. We will discuss the advancements in Natural Language processing (NLP) recently for hate speech identification and include anecdotes from our own research projects. We look at the difficulties in detecting hate speech and discuss how cutting-edge NLP methods can help. We also report the outcomes of our experiments using NLP algorithms to identify hate speech.
Publication details
- DOI
- 10.1109/iccsp60870.2024.10543682
- OpenAlex
- W4399397303
- Document type
- conference-paper
- Language
- EN
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