Comparative study of classifier models for Crime Mitigation and Risk Modelling

Twitter sentiment analysis is an application of sentiment analysis on data from Twitter (tweets) for sentiment extraction. It automatically identifies whether a tweet expresses positive, negative or neutral opinion about and individual or an entity. The aim of this paper is to give detail explanation about the process of Crime mitigation by analyzing sentiment over the data generated by a social platform twitter using machine learning. This study focuses on a comparison done between, two classifier models, for data streamed from twitter. The paper then uses the comparative study for crime mitigation. Classification of sentiment can be done at various level. In our paper, the focus is on Feature level classification. [2]Risk analysis and profiling is then done on the predicted classes.