Online Public Shamming using Machine Learning
Noopura Vaidya, Shivani Chandak, Shubham Dwivedy, Aatif Malik · International Journal of Advanced Research in Science Communication and Technology · 2022
Social Media Platforms involve not millions but billions of users around the globe. Interactions on these easily available social media sites like Twitter have a huge impact on people. Nowadays, there is undesirable negative impact for daily life. These hugely used major platforms of communication have now become a great source of dispersing unwanted data and irrelevant information, Twitter being one of the most extravagant social media platforms in our times, the topmost popular microblogging services is now used as a weapon to share unethical, unreasonable amount of opinions, media. In this proposed work the dishonoring comments, tweets towards people are categorized into 9 types. The tweets are further classifying into one of these types or non- shaming tweets towards people. Observation says out of the multitude of taking an interested clients who posts remarks on a specific occasion, lions share is probably going to modify the person in question. Moreover, it is not the non-shaming devotee who checks the increment quicker but of shaming in twitter.