Behavioral Analysis of User Data on Social Media Applications using Machine Learning Algorithms

Abstract

This paper is developed to predict user behaviour as cyber bullying on social media by using machine learning algorithms in the big data era. In online platform the use of electronic applications to bully a person by sending messages in the form of aggressive behavior of intimidating or threating nature is termed as cyber bullying. These social networks are the result of long process that began around the 1960's which created the first public network. Social media brings together everyone in an online community where one can communicate, share, post, explore, or stay in touch with one another. We can simply say that social media has changed the way we live. Along with the benefits on one side we can't ignore the facts that social media also pose a serious threat to human. In this paper these threats are considered as human aggressive behavior and we have classified it as bullying words and are categorized as filters which include sections like threats, offensive, abusive, harassment, sexual, violence and so on. The use of these social media has been one of the reason for the generation in huge amount of data and in order to manage and solve real-world problems we use big data along with ML. The machine learning techniques like text-classification approach and lexicon based model are used to categorize the collected data from user and detect the presence of cyberbullying activity. Once the bullying activity is detected we can block that comment automatically which then sends alert message to bully and also to cyber-victim, and also keep the count on number of times the bully words are used. As a result, the admin who has all the privileges can monitor the bullying activity based on the count and can take further action whereas the application will have already blocked the comment which contained the bully word thus leaving no harm to victim. The work presented here has profound implications for future studies of cyberbullying and may one-day help to solve the problem of cyberbullying in social media and other online platforms.