Effective Risk Mitigation, Monitoring and Management for Big Data Analytics for Social Media

Crime with time has evolved and now its presence can be seen on various digital platforms. Crime now is spreading easily and quickly through social media platforms, the most common platforms being Twitter and Facebook. These platforms can be easily misused for various types of illegal types of activities as well. [Agarwal, 2011] The aim of this research is to do risk modeling after an analysis of Twitter posts based on certain sentiment analysis. In this research, we analyze posts of several users or a particular user to check whether they can be a cause of concern to the society or not. [Ahlgren, 2016] Every sentiment like happy, sad, anger and other emotions are going to provide scaling of severity in the conclusion of the final table on which machine learning algorithm is applied. This scaling will be of polarity negative,

positive or neutral where less negative means less harmful and higher the value on the scale means it’s more harmful. Positive words are given scales accordingly.