References
[1]. Agarwal, M. K., Ramamritham, K., & Bhide, M. (2012). Real time discovery of dense clusters in highly dynamic graphs: Identifying real world events in highly dynamic environments. Proceedings of the VLDB Endowment, 5(10), 980-991.
[2]. Becker, H., Naaman, M., & Gravano, L. (2011). Beyond Trending Topics: Real-World Event Identification on Twitter. ICWSM, 11(2011), 438-441.
[3]. Cover, T. M., & Thomas, J. A. (2012). Elements of Information Theory. John Wiley & Sons.
[4]. Elder, J. (2013). Inside a Twitter Robot Factory. In Wall Street Journal. Retrieved from https://www.wsj.com/ articles/bogus-accounts-dog-twitter-1385335134
[5]. Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012-1014.
[6]. Just, M. R., Crigler, A. N., Metaxas, P. T., & Mustafaraj, E. (August, 2012). 'It's Trending on Twitter'-An Analysis of the Twitter Manipulations in the Massachusetts 2010 Special Senate Election. APSA 2012 Annual Meeting Paper.
[7]. Kasiviswanathan, S. P., Melville, P., Banerjee, A., & Sindhwani, V. (2011, October). Emerging topic detection th using dictionary learning. In Proceedings of the 20 ACM International Conference on Information and Knowledge Management (pp. 745-754). ACM.
[8]. Lee, K., Palsetia, D., Narayanan, R., Patwary, M. M. A., Agrawal, A., & Choudhary, A. (2011, December). Twitter trending topic classification. In Data Mining Workshops th (ICDMW), 2011 IEEE 11 International Conference on (pp. 251-258). IEEE.
[9]. Lin, J. (1991). Divergence measures based on the Shannon entropy. IEEE Transactions on Information Theory, 37(1), 145-151.
[10]. Lu, R., Xu, Z., Zhang, Y., & Yang, Q. (2012). Life activity modeling of news event on twitter using energy function. In: Tan PN., Chawla S., Ho C.K., Bailey J. (Eds) Advances in Knowledge Discovery and Data Mining (Vol. 7302, pp. 73- 84). PAKDD 2012. Lecture Notes in Computer Science. Springer, Berlin, Heidelberg.
[11]. Morstatter, F., Pfeffer, J., Liu, H., & Carley, K. M. (2013, June). Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose. Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media (pp.400-408).
[12]. Naaman, M., Becker, H., & Gravano, L. (2011). Hip and trendy: Characterizing emerging trends on Twitter. Journal of the Association for Information Science and Technology, 62(5), 902-918.
[13]. Nikolov, S. (2012). Trend or no trend: A novel nonparametric method for classifying time series (Doctoral Dissertation, Massachusetts Institute of Technology).
[14]. Ratkiewicz, J., Conover, M., Meiss, M., Gonçalves, B., Patil, S., Flammini, A. et al. (2010). Detecting and tracking the spread of Astroturf memes in microblog streams. arXiv preprint arXiv:1011.3768.
[15]. Zubiaga, A., Spina, D., Fresno, V., & Martínez, R. (2011, October). Classifying trending topics: A typology of th conversation triggers on twitter. In Proceedings of the 20 ACM International Conference on Information and Knowledge Management (pp. 2461-2464). ACM.