An evolutionary game for the diffusion of rumor in complex networks

Dandan Li, Jing Ma, Zihao Tian and Hengmin Zhu

Physica A: Statistical Mechanics and its Applications, 2015, vol. 433, issue C, 51-58

Abstract: In this paper, we investigate the rumor diffusion process according to the evolutionary game framework. By using three real social network datasets, we find that increasing the judgment ability of individuals could curb the diffusion of rumor effectively. Under the same level of punishment cost, there are more spreaders in the network that has larger average degree. Moreover, the punishment fraction has more significant impact than the risk coefficient on the controlling of rumor diffusion. There exist some optimal risk coefficients and punishment fractions that could help more people refusing to spread rumor. In addition, the effect of the tie strength on the final fraction of spreaders is investigated. The results indicate that the rumor can be suppressed soon if the individuals preferentially select the neighbor either weaker or stronger ties persistently to update their strategy. However, choosing neighbor blindly may promote the spread of rumor. Finally, by comparing three kinds of punishment mechanisms, we show that taking the lead in punishing the higher degree nodes is the most effective measure to reduce the coverage of rumor.

Keywords: Rumor diffusion; Evolutionary game theory; Tie strength; Punishment mechanism (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437115003428
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:433:y:2015:i:c:p:51-58

DOI: 10.1016/j.physa.2015.03.080

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().