Information Diffusion Prediction Based on Time-Series Analysis and Information Novelty

doi:10.13190/jbupt.201301.59.156

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2013, Vol. 36 ›› Issue (1): 59-62.doi: 10.13190/jbupt.201301.59.156

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Information Diffusion Prediction Based on Time-Series Analysis and Information Novelty

CAI Fei, CHEN Hong-hui, SHU Zhen

Science and Technology on Information Systems Engineering Laboratory, College of Information System and Management, Changsha 410073, China

Received:2012-04-22 Revised:2012-10-18 Online:2013-02-28 Published:2013-01-19
Contact: Fei CAI E-mail:caifei@nudt.edu.cn

Abstract

Abstract:

To solve the problem of low precision on information propagation prediction caused by frustrated link prediction in social networks, a new approach, based on time-series analysis, combined with information novelty, is proposed with no requiring the knowledge of social network.When the node is infected, the global influence function of a node is estimated. The overall propagation volume of information is predicted. Simulations on dataset about news articles and blogs show that the proposal can accurately and reliably predict the temporal variations of information diffusion.

Key words: information diffusion prediction, time-series analysis, information novelty, influence propagation

CLC Number:

TP311

CAI Fei, CHEN Hong-hui, SHU Zhen. Information Diffusion Prediction Based on Time-Series Analysis and Information Novelty[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2013, 36(1): 59-62.

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Information Diffusion Prediction Based on Time-Series Analysis and Information Novelty

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