Crime Detection on Social Networking Sites Using Machine learning

Abstract

The information available on social networking sites like Twitter and Facebook has the potential effect in every area of investigation. In this modern age, people want an intelligent system for crime detection on Social Networking Sites (SNS). For this purpose, we need a proper model that detected crime on SNS. In this document, we can discover data about suspects, witnesses, victims, and conspirators. SNS is used as a vehicle for crime, whether it’s for online harassment and bullying, predators finding targets, the determinations of fraud and exploitation, identity theft, or gang recruitment. Social Networking Sites (SNS) can be used as a vehicle to fight crime. Twitter is used extensively all over the world. It is a perfect source for decision support as its users publicly discuss events, emotions, and different topics. In this document for predicting crimes by utilizing the Twitter dataset of Chicago. In this document, we utilized the Naive base algorithm based on conditional probability. This research presents the usage of Naive base algorithm is resolved to the given data of crime. The main purpose of this document is to detected the crimes on social networking sites. Machine learning is used for the analysis prediction and discovery of crime patterns. In this research, applied a model based on Machine learning techniques, to improve the quality of the data and crime detection. In this research, algorithm is also applied for feature to detect crime on social networking sites.