Analysing the Data from Twitter using R

Abstract: Online Social Networks (OSNs) are the powerful medium for communication among the individuals to share their views on disastrous events happening in and around using the opportunities offered by the internet. This paper aims to analyze the meaningful real-time data about the disastrous events obtained from the most popular microblogging OSN �Twitter�. Tweets related to the target event are gathered based on the search query, extracted the keywords from the tweets and then analyzed the significance of those keywords in the events happened during and after the disaster using text mining. The data visualization analytics supported by the statistical software tool �R� is used to explain the discovered phenomena. Tweets are collected on �Jammu and Kashmir Floods� using Twitter API based on various search queries and around 1570 tweet messages were examined. The obtained corpus is then processed using text mining functions provided in �R�. A term document matrix is constructed to know the most frequent words, the distribution of the word frequencies and the association between them. The barplot is plotted to visualize the frequent words. Further the most popular keywords in the tweets and terms contained in the keywords are visualized by constructing a wordcloud from the term document matrix. Keywords: Disastrous Events, Online Social Networks (OSNs), R, Term Document Matrix, Word cloud