Emotive Trending And Tracking of Tweets
Abstract
Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.
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McCreadie, C. Macdonald, I. Ounis, M. Osborne, and S. Petrovic. Scalable distributed event detection for twitter. In Proc. of Big Data, 2013.
Abel, C. Hauff, G.-J. Houben, R. Stronkman, and K. T. Semantics + filtering + search = twitcident. exploring in-formation in social web streams. In Proc. of HT, 2012.
F. Abel, I.Celic, G.-J.Houben and P.Siehndel. Leveraging the semantics of tweets for Adaptive Faceted Search on Twitter. In ISWC, pages 1-17, 2011. Springer.
J. Weng and B.S. Lee. Event Detection in Twitter. In Proc. Of ISCWSM, 2011.
Barbosa and J. Feng. Robust sentiment detection on Twitter from biased and noisy data. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, pages 36_44. Association for Computational Linguistics, 2010.
A.Dong, R. Zhang, P.Kolari, J. Bai, F. Diaz, Y.Chang, Z.Zheng and H.Zha. Time is of the essence: improving recency ranking using twitter data. In proc. Of WWW, pages 331-340, 2010. ACM.
M. S. Bernstein, B.Suh, L.Hong, J.Chen, S.Kairam, and E.H. Chi. Eddi: interactive topic-based browsing of social status streams. In UIST, pages 303-312, 2010. ACM.
M. Mathioudakis and N.Koudas. Twittermonitor: trend detection over the twitter stream. In Proc. Of SIGMOD, pages 1155-1158, 2010.ACM.
Bautin, L. Vijayarenu, and S. Skiena. International sentiment analysis for news and blogs. In Proceedings of the International Conference on Weblogs and Social Media (ICWSM), 2008.
DOI: https://doi.org/10.23956/ijarcsse.v7i11.463
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