Propagation of online news: dynamic patterns

Authors:
Youzhong Wang;Daniel Zeng;Xiaolong Zheng;Feiyue Wang
Affiliations:
The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China;The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China and MIS Department, University of Arizona, Tucson, Arizona;The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China;The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Year:
2009

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Abstract

A large portion of online news articles and postings are not originally created but reprinted or re-posted from other online news sources or portals. In this paper, we analyze the dynamics of online news propagation, using a large collection of Chinese online news activity data. We characterize prominent features of online news diffusion and compare them against the spreading patterns of the epidemic. Several critical factors influencing the news propagation process are identified, including the centrality and selectivity of source portals, and event variability.