Monitoring the Impact of Economic Crisis on Crime in India Using Machine Learning
Abstract Trends of crimes in India keep changing with the growing population and rapid development of towns and cities. The rise in crimes at any place especially crimes against women, children and weaker sections of the society is a worrying factor for the Indian Government. In India, the crime data is maintained by National Crime Records Bureau as well as an application called Crime Criminal Information System is available to make inquiry and generate reports for the crime data. To curb crime, the Police need countless hours to go through the crime data and determine the various factors that affect it. Therefore, there is necessity of tools which can automatically predict the factors that effects the crimes effectively and efficiently. The field of machine learning has emerged in the recent years for this purpose. In this paper, various machine learning techniques have been applied on crime data to monitor the impact of economic crisis on the crime in India. The effect of unemployment rates and Gross District Domestic Product on theft, robbery and burglary has been monitored across districts of various states in India. Further, Granger causality between crime rates and economic indicators has also been calculated. It has been observed from the experimental work that unemployment rate is the major economic factor which affects the crime rate, thus paving the path to control the crime rate by raising more opportunities for the employment.