  Online social media such as Twitter, Facebook, Wikis and Linkedin have made a
great impact on the way we consume information in our day to day life. Now it
has become increasingly important that we come across appropriate content from
the social media to avoid information explosion. In case of Twitter, popular
information can be tracked using hashtags. Studying the characteristics of
tweets containing hashtags becomes important for a number of tasks, such as
breaking news detection, personalized message recommendation, friends
recommendation, and sentiment analysis among others.
  In this paper, we have analyzed Twitter data based on trending hashtags,
which is widely used nowadays. We have used event based hashtags to know users'
thoughts on those events and to decide whether the rest of the users might find
it interesting or not. We have used topic modeling, which reveals the hidden
thematic structure of the documents (tweets in this case) in addition to
sentiment analysis in exploring and summarizing the content of the documents. A
technique to find the interestingness of event based twitter hashtag and the
associated sentiment has been proposed. The proposed technique helps twitter
follower to read, relevant and interesting hashtag.
