A machine learning approach towards social media to tackle cyberbullying
Anjana J Mani, Jinu P. Sainudeen · International journal of advance research, ideas and innovations in technology · 2018
The prevalence of social media is expanding step by step y. People of all age group are terribly interested in social networking. Social media connects people from different parts of the world. However, social media may have some side effects such as cyberbullying, which may have negative impacts on the life of people. Research shows that children and teenagers are the main victims of this cyber attack. Through the social media, people share their thoughts and emotions with their friends. There are large numbers of fraud accounts in social media. Cyberbullying is when someone, harass others on social media sites. Some people use it for cyber attack by making negative comments on others post. One way to tackle this problem is to detect those bullying messages and encrypt it. Machine learning techniques make automatic detection of cyberbullying messages. Weka is a powerfull machine learning tool which can be used for this purpose. A combination of classification and lexical algorithms can detect whether a message is bullying or not. Cyberbullying is a major problem in society since social media has its presence in all fields of modern man’s life.