Citation:

Mohammed Zahir Ali Khan, M.Amuthavaani, R.Kalai Selvi, 2022. "How to Spot and Stop Social Media Bullying Communication", ESP Journal of Engineering & Technology Advancements (ESP-JETA)  2(1): 21-23.

Abstract:

Many internet users now utilise social media platforms to discuss new ideas, learn about the most recent developments, and exchange the most recent updates internationally from one region to another. As it gains popularity, there are still some fundamental limitations on how it can handle abusive or vulgar communications from certain user accounts. The act of a younger kid or adolescent being threatened by another child online through nasty conversations in an effort to make them feel insecure is known as cyberbullying. This is becoming into a pretty significant problem as a result of the hurtful remarks that are increasingly being said to children and young adults on social media. In order to prevent such conversations from spreading to others, we try to develop a machine learning technique for spotting the collection of abusive phrases in chats. By utilising the provided strategy, we will be able to create a good and secure discourse in social media. Here, we created a filter with a Support Vector Machine (SVM) to exclude words that were improperly utilised in speech.

References:

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Keywords:

Social networking sites, cyberbullying, SVM (SVM), interactions that are threatening or offensive, and damage.