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Nov 11, 2022 · Hate Speech Detection using Deep Learning. Last Updated : 11 Nov, 2022. There must be times when you have come across some social media post whose main aim is to spread hate and controversies or use abusive language on social media platforms. As the post consists of textual information to filter out such Hate Speeches NLP comes in handy.
Hate Speech Detection. 175 papers with code • 14 benchmarks • 41 datasets. Hate speech detection is the task of detecting if communication such as text, audio, and so on contains hatred and or encourages violence towards a person or a group of people.
Aug 20, 2019 · As hate speech continues to be a societal problem, the need for automatic hate speech detection systems becomes more apparent. We presented the current approaches for this task as well as a new system that achieves reasonable accuracy.
Mar 11, 2024 · We perform a detailed review to achieve a deep knowledge of the hate speech detection landscape from 2018 to 2023, revealing global incidents of hate speech in 2022–2023. Sixty-six relevant articles were selected for this review.
The paper presents some of the hate speech datasets considered for hate speech detection. Furthermore, the paper discusses different data modalities, namely, textual hate speech detection, multi-modal hate speech detection and multilingual hate speech detection.
We present here a large-scale empirical comparison of deep and shallow hate-speech detection methods, mediated through the three most commonly used datasets. Our goal is to illuminate progress in the area, and identify strengths and weaknesses in the current state-of-the-art.
5 days ago · In conclusion, sentiment analysis and hate speech detection using deep learning algorithms have significant potential in combating online hate speech. By utilizing natural language processing techniques to pre-process data and applying deep learning models for classification, it can accurately identify and remove harmful content from social media platforms.
