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Research on the Model of Word-of-Mouth Communication in Social Networks Based on Dynamic Simulation

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Business Intelligence and Information Technology (BIIT 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 107))

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Abstract

Word-of-mouth communication plays an important role in consumers’ purchasing decisions. With the rapid development of the Internet, social networks have become an important way for word-of-mouth communication. This study draws on the dynamic model of the spread of infectious diseases and establishes a model of word-of-mouth communication in social networks. By analyzing the characteristics of word-of-mouth communication in social networks, the process of withdrawing from the communicator group and becoming a communicator again is introduced. This article uses a dynamic simulation method to simulate and analyze the process of word-of-mouth communication in social networks. The experimental results show that the withdrawal of the communicator group into a communicator again can effectively increase the time of word-of-mouth communication in social networks and reduce the rate of decrease in the popularity of word-of-mouth communication. The simulation analysis of word-of-mouth communication in social networks provides theoretical support for enterprises to make product promotion decisions.

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References

  1. Guerreiro, J., Pacheco, M.: How green trust, consumer brand engagement and green word-of-mouth mediate purchasing intentions. Sustainability. 13, 7877 (2021)

    Article  Google Scholar 

  2. Cheng, X.S.: The paradox of word-of-mouth in social commerce: exploring the juxtaposed impacts of source credibility and information quality on SWOM spreading. Inf. Manage. 58(7), 103505 (2021)

    Article  Google Scholar 

  3. Hussain, S., Ahmed, W., Jafar, R.M.S.: eWOM source credibility, perceived risk and food product customer’s information adoption. Comput. Hum. Behav. 66, 96–102 (2017)

    Article  Google Scholar 

  4. Cai, S.Q., Wang, W., Zhou, P.: Research on the dissemination of negative word-of-mouth information in network communities based on multi-agents. Comput Sci. 43(4), 70–75 (2016)

    Google Scholar 

  5. Cai, S.Q., Yuan, Q., Zhou, P.: Research on the linear threshold propagation model of negative word of mouth under corporate response. J. Syst. Eng. 32(2), 145–155 (2017)

    Google Scholar 

  6. Deng, W.H., Yi, M.: Research on the tree communication of online community word-of-mouth information based on the information diffusion cascade theory. Chinese J. Manage. 14(2), 254–260 (2017)

    MathSciNet  Google Scholar 

  7. Li, P., Yang, X., Yang, L.X.: The modeling and analysis of the word-of-mouth marketing. Phys. A Statist. Mech. Appl. 493, 1–16 (2018)

    Article  MathSciNet  Google Scholar 

  8. Edmond, A., Michael, A., Susan, L.A.: An approach for combining ethical principles with public opinion to guide public policy. Artif. Intell. 287, 303–349 (2010)

    MathSciNet  MATH  Google Scholar 

  9. Li, Z., Xu, Y., Li, K.: The influence factors of collective intelligence emergence in knowledge communities based on social network analysis. Int. J. Intell. Syst. 9(1), 23–43 (2019)

    Google Scholar 

  10. Yu, W., Shanshan, C., Xinchu, F.U.: Review and prospect of propagation dynamics models. Commun. Appl. Math. Comput. 32(2), 267–294 (2018)

    MathSciNet  MATH  Google Scholar 

  11. Thomas, W.C.: Equivalent probability density moments determine equivalent epidemics in a sirs model with temporary immunity. Theor. Popul. Biol. 113, 1–9 (2017)

    Article  Google Scholar 

  12. Pu, C., Li, S., Yang, X.X.: Traffic-driven SIR epidemic spreading in networks. Phys. A Statist. Mech. Appl. 446, 29–137 (2015)

    MATH  Google Scholar 

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Acknowledgment

This research was supported by the Heilongjiang philosophy and Social Science Fund Project (21GLC186).

Author information

Authors and Affiliations

  1. Harbin University of Commerce, Harbin, 150028, China

    Zhipeng Fan, Wen Hu, Wei Liu & Ming Chen

  2. Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing, Harbin, 150028, China

    Zhipeng Fan, Wen Hu & Ming Chen

Authors
  1. Zhipeng Fan
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  2. Wen Hu
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  3. Wei Liu
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  4. Ming Chen
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Corresponding author

Correspondence to Zhipeng Fan .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Yaoqun Xu

  3. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Zhijie Zhao

  4. Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

    Sabah Mohammed

  5. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Zhipeng Fan

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Fan, Z., Hu, W., Liu, W., Chen, M. (2022). Research on the Model of Word-of-Mouth Communication in Social Networks Based on Dynamic Simulation. In: Hassanien, A.E., Xu, Y., Zhao, Z., Mohammed, S., Fan, Z. (eds) Business Intelligence and Information Technology. BIIT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 107. Springer, Cham. https://doi.org/10.1007/978-3-030-92632-8_50

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