Cyberbullying is the aggressive pressure or harassment produce through electronic devices like laptops, desktop or computer, smart phones, and tablets. The harassment can occur in the environment of social networking sites, chat rooms, and gaming platforms where people can view and take part in the exchanging of their thoughts. The different kind of cyberbullying or harassment creates the humiliation through hateful comments on digital platforms/apps, or through SMS or messaging. It involves the sending posting, or sharing negative, disgusting, nasty or wrong information about another individual for causing embarrassment and the malicious and unjustified harming of a person's good reputation. Machine learning algorithms give a chance to find successfully predicting, detecting and preventing undesirable, harmful and unwanted opinions of human behavior, such as cyberharassment. It gives the pivotal information on new ways in the way of detecting and preventing antagonistic or violent human behavior, including cyber harassment detection and prevention in online social environmental sites. ML algorithms gives an prospect to completely expect, detect and prevent hurtful attitude of human behavior, such as cyber bullying. A model is proposed to detect and prevent the negative opinion in social media using Classification model algorithms. Profanity detection library function and Natural Language Processing are used to detect and prevent the negative opinions in the social media. This proposed model is helpful for the Government to identify the negative opinions given by the users in the social media and they can take actions. The development of such an application has the ability to stop and reduce the rate of cyberbullying that has been happening social media.
Read full abstract