An Evolution Model of Rumor Spreading Based on WeChat Social Circle
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
With the rapid development of the Internet and the Mobile Internet, social communication based on thenetwork has become a life style for many people. WeChat is an online social platform, for about one billionusers, therefore, it is meaningful to study the spreading and evolution mechanism of the rumor on the WeChatsocial circle. The Rumor was injected into the WeChat social circle by certain individuals, and the communicationand the evolution occur among the nodes within the circle; after the refuting-rumor-information injectedinto the circle, subsequently, the density of four types of nodes, including the Susceptible, the Latent, theInfective, and the Recovery changes, which results in evolving the WeChat social circle system. In the study, theevolution characteristics of the four node types are analyzed, through construction of the evolution equation. The evolution process of the rumor injection and the refuting-rumor-information injection is simulatedthrough the structure of the virtual social network, and the evolution laws of the four states are depicted byfigures. The significant results from this study suggest that the spreading and evolving of the rumors are closelyrelated to the nodes degree on the WeChat social circle.
Abstract
With the rapid development of the Internet and the Mobile Internet, social communication based on thenetwork has become a life style for many people. WeChat is an online social platform, for about one billionusers, therefore, it is meaningful to study the spreading and evolution mechanism of the rumor on the WeChatsocial circle. The Rumor was injected into the WeChat social circle by certain individuals, and the communicationand the evolution occur among the nodes within the circle; after the refuting-rumor-information injectedinto the circle, subsequently, the density of four types of nodes, including the Susceptible, the Latent, theInfective, and the Recovery changes, which results in evolving the WeChat social circle system. In the study, theevolution characteristics of the four node types are analyzed, through construction of the evolution equation. The evolution process of the rumor injection and the refuting-rumor-information injection is simulatedthrough the structure of the virtual social network, and the evolution laws of the four states are depicted byfigures. The significant results from this study suggest that the spreading and evolving of the rumors are closelyrelated to the nodes degree on the WeChat social circle.
참고문헌 (25)
- Wen-Chi Hou, "Utilizing Fragmented Bandwidth in a Staggered Striping Multimedia System", JIPS(Journal of Information Processing Systems), 4(1), pp.1~8 (2008), 한국정보처리학회
- D. J. Watts, "Collective dynamics of small-world networks", Nature, 393(6684), pp.440~442 (1998)
- A. L. Barabasi, "Emergence of scaling in random networks", Science, 286(5439), pp.509~512 (1999)
- R. Kumar, "Structure and evolution of online social networks", Proceeding of the 12th ACM SIGKDD International Conference on Knowledge Discovery And Data Mining, pp.611~617 (2006)
- H. Hu, "Evolution of a large online social network", Physics Letters A, 373(12-13), pp.1105~1110 (2009)
- A. Mislove, "Measurement and analysis of online social networks", Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, pp.29~42 (2007)
- H. Chun, "Comparison of online social relations in terms of volume vs. interaction: a case study of cyworld", Proceedings of the 8th ACM SIGCOMM Conference on Internet Measurement, pp.57~70 (2008)
- J. N. Kapeerer, "Rumor: The World's Oldest Media" (2008), Shanghai People’s Publishing House
- R. K. Garrett, "Troubling consequences of online political rumoring", Human Communication Research, 37(2), pp.255~274 (2011)
- G. L. Cohen, "When beliefs yield to evidence : reducing biased evaluation by affirming the self", Personality and Social Psychology Bulletin, 26(9), pp.1151~1164 (2000)
- D. J. Daley, "Epidemics and rumours", Nature, 204(4963), pp.1118~1118 (1964)
- D. Maki, "Mathematical Models and Applications" (1973), Prentice-Hall
- B. Doerr, "Social networks spread rumors in sublogarithmic time", Electronic Notes in Discrete Mathematics, 38, pp.303~308 (2011)
- D. H. Zanette, "Critical behavior of propagation on small-world networks", Physical Review E, 64(5) (2001)
- D. H. Zanette, "Dynamics of rumor propagation on small-world networks", Physical Review E, 65(4) (2002)
- Y. Moreno, "Dynamics of rumor spreading in complex networks", Physical Review E, 69(6) (2004)
- Z. F. Pan, "Simulation investigation on rumor spreading on scale-free network with tunable clustering", Journal of System Simulation, 18(8), pp.2346~2348 (2006)
- "Modeling the spread of influence on the blogosphere" (2006)[URL]
- Z. Y. Zheng, "Study on microblog propagation model based on analysis of user behavior", Computer Science, 43(12), pp.41~46 (2016)
- Z. J. Song, "Influence of authoritative information release on rumors microblog spreading in emergency events", Journal of Intelligence, 35(12), pp.41~47 (2016)
- D. Lu, "Based on the double S model research in WeChat rumors spreading", Mathematics in Practice and Theory, 2017(16), pp.157~163 (2017)
- Y. X. Luo, "A comparative study of spread of Weibo and WeChat rumors from the perspective of public opinion", Journalism Knowledge, 2014(4), pp.6~8 (2014)
- W. Dou, "A P2P approach for global computing", Proceedings International Parallel and Distributed Processing Symposium (2003)
- Z. Liu, "Paradropper: a general-purpose global computing environment built on peer-to-peer overlay network", Proceedings of the 23rd International Conference on Distributed Computing Systems Workshops, pp.954~957 (2003)
- W. Dou, "A rumor-spreading analog on unstructured P2P broadcast mechanism", Journal of Computer Research and Development, 2004(9), pp.1460~1465 (2004)