TY - GEN
T1 - Is that twitter hashtag worth reading
AU - Anusha, A.
AU - Singh, Sanjay
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/8/10
Y1 - 2015/8/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84960956332&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84960956332&partnerID=8YFLogxK
U2 - 10.1145/2791405.2791526
DO - 10.1145/2791405.2791526
M3 - Conference contribution
AN - SCOPUS:84960956332
VL - 10-13-August-2015
T3 - ACM International Conference Proceeding Series
SP - 272
EP - 277
BT - Proceeding of the 3rd International Symposium on Women in Computing and Informatics, WCI 2015
A2 - Mitra, Sushmita
A2 - Bedi, Punam
A2 - McIntosh, Suzanne
A2 - M.S., Rajasree
A2 - Nair, Indu
PB - Association for Computing Machinery (ACM)
T2 - 3rd International Symposium on Women in Computing and Informatics, WCI 2015
Y2 - 10 August 2015 through 13 August 2015
ER -