Detection of crime and non-crime tweets using Twitter

Abstract: As the speedy growth of Twitter in social media, researchers get attracted towards the use of social media data for analysis. Twitter is one of the widely used social media platform to express thoughts. This paper approaches for analyzing tweets using sentiment mining in which classify highly unstructured data on Twitter and second is data mining. There are 500 million users of Twitter. The limit of character in twitter is 140 character because of this user uses shorthand notation example �ok� can be used as �kk�. Analysis of tweets contains misspellings and grammatical error.

Keywords: Social network, natural language processing, Machine Learning, sentiment analysis and data mining.