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International Journal of Engineering Science and Advanced Technology (IJESAT)Vol 24 Issue 06, JUNE, 2024HATE SPEECH DETECTION IN ONLINE SHORTFORM VIDEOS THROUGH AUDIO CLASSIFICATION 1B.Nirupama, 2Nara
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Identify the content that needs to be analyzed for hate speech.
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Use a reliable hate speech detection tool or algorithm.
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Input the text or data into the detection system.
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Review the results provided by the tool.
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Flag or categorize the content based on the detection results.
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Take necessary actions based on the outcomes, such as reporting or moderating.

Who needs hate speech detection in?

01
Social media platforms for content moderation.
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Online communities to maintain a safe environment.
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Law enforcement agencies for investigating hate crimes.
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Educational institutions to promote respectful dialogue.
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NGOs and advocacy groups focused on anti-discrimination efforts.
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Hate speech detection refers to the process of identifying and categorizing speech that incites violence or prejudicial behavior against individuals or groups based on attributes such as race, religion, ethnicity, gender, or sexual orientation.
Entities such as social media platforms, online publishers, and organizations that manage user-generated content are often required to implement hate speech detection measures to comply with legal regulations and community guidelines.
To fill out hate speech detection, organizations typically need to provide details on the algorithms or methodologies employed for detection, the training data used, the thresholds for classification, and the reporting procedures following detection.
The purpose of hate speech detection is to mitigate the spread of harmful content, protect targeted communities, ensure compliant use of platforms, and foster a safer online environment.
Organizations must report information such as the number of detected hate speech instances, actions taken in response, user appeals, and the effectiveness of detection algorithms in identifying harmful content.
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