Machine Learning based Analysis on Human Aggressiveness and Reactions towards Uncertain Decisions

Tweet data can be processed as a useful information. Social media sites like Twitter, Facebook, Google+ are rapidly growing popularity. These social media sites provide a platform for people to share and express their views about daily routine life, have to discuss on particular topics, have discussion with different communities, or connect with globe by posting messages. Tweets posted on twitter are expressed as opinions. These opinions can be used for different purposes such as to take public views on uncertain decisions such as Muslim ban in America, War in Syria, American Soldiers in Afghanistan etc. These decisions have direct impact on user's life such as violations & aggressiveness are common causes. For this purpose, we will collect opinions on some popular decision taken in past decade from twitter. We will divide the sentiments into two classes that is anger (hatred) and positive. We will propose a hypothesis model for such data which will be used in future. We will use Support Vector Machine (SVM), Naive Bayes (NB), and Logistic Regression (LR) classifier for text classification task. Further-more, we will also compare SVM results with NB, LR. Research will help us to predict early behaviors & reactions of people before the big consequences of such decisions.