在线社交媒体信息冗余现象建模与实证研究

doi:10.11959/j.issn.2096-0271.2018050

Big Data Research ›› 2018, Vol. 4 ›› Issue (5): 50-61.doi: 10.11959/j.issn.2096-0271.2018050

• TOPIC：PRACTICAL INNOVATIONS OF BIG DATA • Previous Articles Next Articles

Modeling and empirical research of information redundancy on online social media

Shuo QIN¹,Xin LU^1,^2,³(),Fanhui MENG⁴,Yanqing HU⁴

¹ College of Systems Engineering,National University of Defense Technology,Changsha 410073,China
² School of Business,Central South University,Changsha 410083,China
³ Department of Public Health Sciences,Karolinska Institute,Stockholm 17177,Sweden
⁴ School of Data and Computer Science,Sun Yat-sen University,Guangzhou 510006,China

Online:2018-09-15 Published:2018-12-10
Supported by:
The National Natural Science Foundation of China(71522014);The National Natural Science Foundation of China(71771213);The National Natural Science Foundation of China(61773412);The National Natural Science Foundation of China(U1711265)

Abstract

Abstract:

To learn more about redundancy phenomenon,a measurement to quantify this redundancy was proposed and the probability of individual redundancy in the process of information diffusion was deduced.Using simulated networks,how information propagation rate,network density,clustering coefficient affect information redundancy was investigated.The diffusion characteristics of redundant information through the actual data of Sina Weibo was observed and the perspective of information redundancy in advertising promotion and product marketing was discussed from marketing.The findings provide a new perspective for further understanding of the information diffusion characteristics of online social media.

Key words: social network, online social media, information diffusion, information redundancy

CLC Number:

N941.3

Shuo QIN, Xin LU, Fanhui MENG, Yanqing HU. Modeling and empirical research of information redundancy on online social media[J]. Big Data Research, 2018, 4(5): 50-61.

Figures/Tables 11

References 19

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网络名称	节点数N/个	边数M/条	平均度k	最大度k_max	平均集聚系数C
Facebook网络	4 039	88 234	43	1 045	0.605 5
在线音乐社交网络	41 773	125 826	6	112	0.091 2
维基百科投票网络	7 115	103 689	26	1 065	0.140 9

Modeling and empirical research of information redundancy on online social media

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