Machine Learning
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Exact indexing of dynamic time warping
Knowledge and Information Systems
Proceedings of the VLDB Endowment
Twitter power: Tweets as electronic word of mouth
Journal of the American Society for Information Science and Technology
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Patterns of temporal variation in online media
Proceedings of the fourth ACM international conference on Web search and data mining
All of Nonparametric Statistics
All of Nonparametric Statistics
Proceedings of the 20th international conference on World wide web
Hip and trendy: Characterizing emerging trends on Twitter
Journal of the American Society for Information Science and Technology
Dynamical classes of collective attention in twitter
Proceedings of the 21st international conference on World Wide Web
Modeling and predicting behavioral dynamics on the web
Proceedings of the 21st international conference on World Wide Web
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Microblogging disseminates realtime information through dynamic user interactions. While it is intuitive that such interactions may generate patterns, it is difficult to identify and characterize them in satisfactory detail. In this paper, we propose using a combination of dynamic graphs and time-series to study the dynamics and collective behaviors in microblogging. To enable automatic pattern identification, a distance metric is developed to incorporate the heterogeneous aspects of the dynamical interactions. We demonstrate the effectiveness of the proposed approach using a month long Twitter dataset and show that the new representation and distance metric are both essential for discovering the patterns of collective microblogging, such as propagation of breaking news, advertisement, social movement, and interest group formation.