2015 WhyItHappenedIdentifyingandMode

• (Rong et al., 2015) ⇒ Yu Rong, Hong Cheng, and Zhiyu Mo. (2015). “Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events.” In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015). ISBN:978-1-4503-3664-2 doi:10.1145/2783258.2783305

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Cited By

• http://scholar.google.com/scholar?q=%222015%22+Why+It+Happened%3A+Identifying+and+Modeling+the+Reasons+of+the+Happening+of+Social+Events
• http://dl.acm.org/citation.cfm?id=2783258.2783305&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; event cascade; external influence; information diffusion; intrinsic influence; [[poisson process; social influence

Abstract

In nowadays social networks, a huge volume of content containing rich information, such as reviews, ratings, microblogs, etc., is being generated, consumed and diffused by users all the time. Given the temporal information, we can obtain the event cascade which indicates the time sequence of the arrival of information to users. Many models have been proposed to explain how information diffuses. However, most existing models cannot give a clear explanation why every specific event happens in the event cascade. Such explanation is essential for us to have a deeper understanding of information diffusion as well as a better prediction of future event cascade.

In order to uncover the mechanism of the happening of social events, we analyze the rating event data crawled from Douban.com, a Chinese social network, from year 2006 to 2011. We distinguish three factors: social, external and intrinsic influence which can explain the emergence of every specific event. Then we use the mixed Poisson process to model event cascade generated by different factors respectively and integrate different Poisson processes with shared parameters. The proposed model, called Combinational Mixed Poisson Process (CMPP) model, can explain not only how information diffuses in social networks, but also why a specific event happens. This model can help us to understand information diffusion from both macroscopic and microscopic perspectives. We develop an efficient Classification EM algorithm to infer the model parameters. The explanatory and predictive power of the proposed model has been demonstrated by the experiments on large real data sets.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2015 WhyItHappenedIdentifyingandMode	Hong Cheng Yu Rong Zhiyu Mo			Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events				10.1145/2783258.2783305		2015