Challenges for Hate Speech Recognition System: Approach based on Solution

Hate speech spreads as the quantity of content on the internet grows. Automated methods for identifying hate speech in text face a number of challenges, which we investigate and assess. Language complexity, differing views on what constitutes hate speech, and data availability restrictions for algor...

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Bibliographic Details
Published in2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) pp. 699 - 704
Main Authors Pawar, A.B., Gawali, Pranav, Gite, Mangesh, Jawale, M. A., William, P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 07.04.2022
Subjects
Automation
Cognition
Face recognition
Hate speech
Language Complexity
Speech recognition
Support vector machines
SVM
Training
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Summary:Hate speech spreads as the quantity of content on the internet grows. Automated methods for identifying hate speech in text face a number of challenges, which we investigate and assess. Language complexity, differing views on what constitutes hate speech, and data availability restrictions for algorithm training and testing are some of the difficulties. As a result, it may be difficult to decipher the reasoning behind the decisions made by many current methods. With our multiview SVM technique, we give near-state of the art SVM results that are easier to comprehend than neural approaches. In addition, we look at the challenges that this endeavour faces on a technological and practical level.
DOI:10.1109/ICSCDS53736.2022.9760739