Analysis and visualization of Twitter data using k-means clustering

A social structure of individuals related directly or indirectly on the basis of some common factor like similar likings etc. is a social network. In order to understand the behavior and structure of a social network we need to study the network and this study is called social network analysis. There has been a rapid increment in the research and study of data mining community and social network analysis. There are various social networking sites available on internet like LinkedIn, Facebook, Instagram, Twitter, Google and many more. Interactions over such sites produces huge amount of data because billions of active users maintain their accounts. Hence, it is a tedious task to analyze the complex data. It is of great importance for academic and business to analyze such online social communities and predicting their behavior. In this paper, we are concentrating on Twitter data. R language is used for acquisition, preprocessing, analyzing and visualization of the twitter data. Twitter data is extracted, preprocessed and then clustered based on the geotagged information.