Abstract

Abstract: Twitter is a popular online social networking service with over 300 million users that share a massive amount of information every day. The ability for users to tweet about events, conditions, sentiments, views, or even something new in real time is Twitter's most important feature. There is no structure in place to ensure truth or trustworthiness: anyone can say whatever they want. The type of Twitter war may be a simple way to attack your adversaries for them to attack. Several applications of machine learning and hate speech identification to aid in the detection of Sarcasm and shamming tweets were covered in this survey. With the growth of online social networks and the emergence of public shaming events, there is a needto analyze shaming tweets, categories shaming tweets into various groups, and combat shaming tweets by banning them.Keywords: K-nearest neighbours (KNN);Random forest(RF);Naive Bayes(NB);Application programming interface(API);Online social networks (OSNs).