Extraction, summariz ation and sentiment analysis of trending topics on Twitter

Abstract

Twitter is amongst the most popular social networking and micro-blogging service today with over a hundred million users generating a wealth of information on a daily basis. This paper explores the automatic mining of trending topics on Twitter, analyzing the sentiments and generating summaries of the trending topics. The trending topics extracted are compared to the day's news items in order to verify the accuracy of the proposed approach. Results indicate that the proposed method is exhaustive in listing out all the important topics. The salient feature of the proposed technique is its ability to refine the trending topics to make them mutually exclusive. Sentiment analysis is carried out on the trending topics retrieved in order to discern mass reaction towards the trending topics and finally short summaries for all the trending topics are formulated that provide an immediate insight to the reaction of the masses towards every topic.