Network Opinion Evolution with Considering the Herding Effect Influence

doi:10.13190/j.jbupt.2014.s1.003

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2014, Vol. 37 ›› Issue (s1): 12-17.doi: 10.13190/j.jbupt.2014.s1.003

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Network Opinion Evolution with Considering the Herding Effect Influence

ZHANG Feng¹, GAO Feng², WU Bin¹, WANG Bai¹

1. Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. Network Technology Research Institute, China Unicom, Beijing 100048, China

Received:2013-12-28 Online:2014-06-28 Published:2014-06-28
Supported by:

Abstract

Abstract:

In order to solve the issue that the individual driving force lacks in traditional opinion model, a dynamics opinion model based on expected attraction and trust neighbor mass(DOET) model-dynamics opinion model based on expected attraction and trust neighbor mass is proposed. It combines exception-traction and herding effect which can establish state transfer and three kinds of opinion decision. The opinion is formed through DOET model with considering two factors of internal expectation attraction and trust neighbor mass. Experiments show that this model can simulate unification, polarization and mild concussion of opinion under influence of exception-traction and herding effect; because of network structure and distribution of initial opinion, the "Compliance" node is not disappeared but kept in existence. Also, DOET model is correspond to the characteristics of opinion formation and individual interaction with comparing existing opinion model. Consequently, this model can express internal disciplines also can be referred to the network analysis in opinion formation.

Key words: opinion dynamics, herding effect, bounded confidence, complex network

CLC Number:

TP391.9

ZHANG Feng, GAO Feng, WU Bin, WANG Bai. Network Opinion Evolution with Considering the Herding Effect Influence[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2014, 37(s1): 12-17.

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Network Opinion Evolution with Considering the Herding Effect Influence

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