- (Matsubara et al., 2012) ⇒ Yasuko Matsubara, Yasushi Sakurai, B. Aditya Prakash, Lei Li, and Christos Faloutsos. (2012). “Rise and Fall Patterns of Information Diffusion: Model and Implications.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339537
The recent explosion in the adoption of search engines and new media such as blogs and Twitter have facilitated faster propagation of news and rumors. How quickly does a piece of news spread over these media? How does its popularity diminish over time? Does the rising and falling pattern follow a simple universal law?
In this paper, we propose SpikeM, a concise yet flexible analytical model for the rise and fall patterns of influence propagation. Our model has the following advantages: (a) unification power: it generalizes and explains earlier theoretical models and empirical observations; (b) practicality: it matches the observed behavior of diverse sets of real data; (c) parsimony: it requires only a handful of parameters; and (d) usefulness: it enables further analytics tasks such as forecasting, spotting anomalies, and interpretation by reverse-engineering the system parameters of interest (e.g. quality of news, count of interested bloggers, etc.).
Using SpikeM, we analyzed 7.2GB of real data, most of which were collected from the public domain. We have shown that our SpikeM model accurately and succinctly describes all the patterns of the rise-and-fall spikes in these real datasets.
|2012 RiseandFallPatternsofInformatio||Yasuko Matsubara|
B. Aditya Prakash
|Rise and Fall Patterns of Information Diffusion: Model and Implications||10.1145/2339530.2339537||2012|
|Author||Yasuko Matsubara +, Yasushi Sakurai +, B. Aditya Prakash +, Lei Li + and Christos Faloutsos +|
|proceedings||Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining +|
|title||Rise and Fall Patterns of Information Diffusion: Model and Implications +|