Modeling for Information Transmission of Consumer Products Quality and Safety Based on the Social Network

  • Yingcheng Xu
  • Xiaohong Gao
  • Ming Lei
  • Huali Cai
  • Yong Su
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 355)


This chapter considers the Information Transmission of Consumer Products Quality…?>web information of consumer products quality and safety as research object. As to the transmission characteristics of social network, we established an information transmission model without the government’s intervention based on the social network to analyze the relationship of parameters in terms of the information transmission by means of simulation. The results show that the proposed model is more effective and feasible.


Web information Consumer products quality safety Information transmission model Social network 



This research is supported by the National Natural Science Foundation of China (Grant Nos. 71301152, 71271013 and 71301011), National Social Science Foundation of China (Grant No. 11AZD096), National Key Technology R&D Program of the Ministry of Science and Technology (Grant Nos. 2013BAK04B02 and 2013BAK04B04), Quality Inspection Project (Grant No. 201410309), and China Postdoctoral Science Foundation (Grants Nos. 2013T60091 and 2012M520008).


  1. 1.
    Sarafidis Y. What have you done for me lately-release of information and strategic manipulation of memories. Econ J. 2007;117(3):307–26.CrossRefGoogle Scholar
  2. 2.
    Isham V, Harder S, Nekovee M. Stochastic epidemics and rumors on finite random networks. Physica A. 2010;389:561–76.CrossRefGoogle Scholar
  3. 3.
    Becker H, Naaman M, Gravano L. Learning similarity metrics for event identification in social media. In: Proceedings of the third ACM international conference on Web search and data mining, New York, USA, DBLP, 2010. p. 291–300.Google Scholar
  4. 4.
    Zhang YC, Liu Y, Zhang HF, et al. The research of information dissemination model on online social network. Acta Phys Sin. 2011;60(5):60–6.Google Scholar
  5. 5.
    Xie MS, Jia Z. Simulating the spreading of two competing public opinion information on complex network. Appl Math. 2012;3:1074–8.CrossRefGoogle Scholar
  6. 6.
    Wang R, Jin YS, Li F. A review of microblogging marketing based on the complex network theory. In: 2011 International conference in electrics, communication and automatic control proceedings. New York: Springer; 2012. p. 1053–60.Google Scholar
  7. 7.
    Jalili M. Social power and opinion formation in complex networks. Phys A Stat Mech Appl. 2013;392(4):959–66.CrossRefMathSciNetGoogle Scholar
  8. 8.
    Zhang H, Wang D, Wang L, Bi Z, Chen Y. A semantics-based method for clustering of Chinese web search results. Enterp Inf Syst. 2014;8(1):147–65.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Yingcheng Xu
    • 1
  • Xiaohong Gao
    • 1
  • Ming Lei
    • 2
  • Huali Cai
    • 1
  • Yong Su
    • 1
  1. 1.Quality Management BranchChina National Institute of StandardizationBeijingChina
  2. 2.Quality and Technical Review CenterXi’anChina

Personalised recommendations