Skip to main content
SpringerLink
Log in

The Dynamics of Two-State Public Opinion Propagation On Signed Networks

  • Published:
Journal of Systems Science and Complexity Aims and scope Submit manuscript

Abstract

The formation of public opinion on the network is a hot issue in the field of complex network research, and some classical dynamic models are used to solve this problem. The signed network is a particular form of the complex network, which can adequately describe the amicable and hostile relationships in complex real-world systems. However, the methods for studying the dynamic process of public opinion propagation on signed networks still require to be further discussed. In this paper, the authors pay attention to the influence of negative edges in order to design a two-state public opinion propagation mechanism suitable for signed networks. The authors first set the interaction rules between nodes and the transition rules of node states and then apply the model to synthetic and real-world signed networks. The simulation results show that there is a critical value of the negative edge ratio. When the negative edge ratio exceeds this critical value, the evolutionary result of public opinion will change from a consistent state to a split state. This conclusion is also consistent with the distribution result of opinions within communities in the signed network. Besides, the research on the network structural balance shows that the model makes the network evolve in a more balanced direction.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Toft J, Denmark: Potential polarization or consensus?, Journal of Risk Research, 2000, 3(3): 227–235.

    Article  Google Scholar 

  2. Lindh J, Fbrega J, and Gonzlez J, La fragilidad de los consensos: Polarizacin ideolgica en el Chile Post Pinochet, Revista Ciencia Poltica, 2019, 39: 99–127.

    Google Scholar 

  3. Van Gunten T S, Martin J L, and Teplitskiy M, Consensus, polarization, and alignment in the economics profession, Sociological Science, 2016, 3: 1028–1052.

    Article  Google Scholar 

  4. Li L, Scaglione A, Swami A, et al., Consensus, polarization and clustering of opinions in social networks, IEEE Journal on Selected Areas in Communications, 2013, 31(6): 1072–1083.

    Article  Google Scholar 

  5. Lee D, Chang C, and Liu Y, Consensus and polarization of binary opinions in structurally balanced networks, IEEE Transactions on Computational Social Systems, 2016, 3(4): 141–150.

    Article  Google Scholar 

  6. Zeng J P, Zhang S Y, Wu C R, et al., Modelling topic propagation over the Internet, Mathematical and Computer Modelling of Dynamical Systems, 2009, 15(1): 83–93.

    Article  Google Scholar 

  7. Canning A, Ising spin models of partially connected neural networks, Dissertation from University of Edinburgh, 1988.

  8. Xu Z, Dong W, and Srihari S, Using social dynamics to make individual predictions: Variational inference with a stochastic kinetic model, Proceedings of 29th Conference on Neural Information Processing Systems, Montreal, Canada, 2016.

  9. Tang J, Chang Y, Aggarwal C, and Liu H, A survey of signed network mining in social media, ACM Computing Surveys, 2016, Article 42, 37 pages, DOI: https://doi.org/10.1145/2956185.

  10. Dorogovtsev S N, Goltsev A V, and Mendes J F, Ising model on networks with an arbitrary distribution of connections, Physical Review E, 2002, 66(1–2): 016104.

    Article  Google Scholar 

  11. Herrero C P, Ising model in scale-free networks: A Monte Carlo simulation, Physical Review E, 2004, 69(6 Pt 2): 067109.

    Article  Google Scholar 

  12. Sumour M A and Shabat M M, Monte Carlo simulation of Ising model on directed Barabasi-Albert network, International Journal of Modern Physics C, 2005, 16(4): 585–589.

    Article  Google Scholar 

  13. Giuraniuc C V, Hatchett J P L, Indekeu J O, et al, Trading interactions for topology in scale-free networks, Physical Review Letters, 2005, 95(9): 098701.

    Article  Google Scholar 

  14. Barrat A and Weight M, On the properties of small-world network models, European Physical Journal B Condensed Matter and Complex Systems, 2000, 13(3): 547–560.

    Article  Google Scholar 

  15. Castellano C, Vilone D, and Vespignani A, Incomplete ordering of the voter model on small-world networks, EPL, 2003, 63(1): 153–158.

    Article  Google Scholar 

  16. Galam S, Minority opinion spreading in random geometry, The European Physical Journal B, 2002, 25(4): 403–406.

    Google Scholar 

  17. Sznajd-Weron K and Sznajd J, Opinion evolution in closed community, International Journal of Modern Physics C, 2011, arXiv: cond-mat/0101130.

  18. Deffuant G, Neau D, Amblard F, et al., Mixing beliefs among interacting agents, Advances in Complex Systems, 2000, 3(1–4): 87–98.

    Article  Google Scholar 

  19. Parisien C, Anderson C H, and Eliasmith C, Solving the problem of negative synaptic weights in cortical models, Neural Computation, 2008, 20(6): 1473–1494.

    Article  MathSciNet  Google Scholar 

  20. Ghosn F, Palmer G, and Bremer S A, The MID3 data set, 1993–2001: Procedures, coding rules, and description, Conflict Management and Peace Ence, 2004, 21(2): 133–154.

    Article  Google Scholar 

  21. Girdhar N and Bharadwaj K K, Signed social networks: A survey, Advances in Computing and Data Sciences, Springer, Singapore, 2016.

    Google Scholar 

  22. Leskovec J, Huttenlocher D, and Kleinberg J, Signed networks in social media, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, New York, USA, 2010, 1361–1370.

  23. Fan P Y, Wang H, Li P, et al., Analysis of opinion spreading in homogeneous networks with signed relationships, Journal of Statistical Mechanics Theory and Experiment, 2012, 2012(8): 08003.

    Article  Google Scholar 

  24. Li W, Fan P Y, Li P, et al., An opinion spreading model in signed networks, Modern Physics Letters B, 2013, 27(12): 50084.

    Article  MathSciNet  Google Scholar 

  25. Saeedian M, Azimi-Tafreshi N, Jafari G R, et al., Epidemic spreading on evolving signed networks, Physical Review E, 2017, 95: 022314.

    Article  MathSciNet  Google Scholar 

  26. Li W, Ma Y H, and Xue R R, The application of signed networks in the Moon-Cake opinion network, International Conference on Industrial Engineering and Information Technology, Tianjin, China, 2014.

  27. Li L B, Fan Y, Zeng A, et al., Binary opinion dynamics on signed networks based on Ising model, Physica A: Statistical Mechanics and Its Applications, 2019, 433–442.

  28. Proskurnikov A V, Matveev A S, and Cao M, Opinion dynamics in social networks with hostile camps: Consensus vs. polarization, IEEE Transactions on Automatic Control, 2016, 61(6): 1524–1536.

    Article  MathSciNet  Google Scholar 

  29. Proskurnikov A V and Cao M, Polarization in coopetitive networks of heterogeneous nonlinear agents, IEEE 55th Conference on Decision and Control, Las Vegas, NV, 2016.

  30. Tajfel H, Differentiation between social groups: Studies in the social psychology of intergroup relations, American Journal of Sociology, 1981, 86(5): 1193–1194.

    Article  Google Scholar 

  31. Turner J C and Oaks P J, The significance of the social identity concept for social psychology with reference to individualism, interactionism, and social influence, The British Journal of Social Psychology, 2011, 25(3): 237–252.

    Article  Google Scholar 

  32. Brewer M B, The social psychology of intergroup relations: Social categorization, ingroup bias, and outgroup prejudice, Social Psychology: Handbook of Basic Principles, The Guilford Press, New York, NY, US, 2007.

    Google Scholar 

  33. Tetlock P E, Skitka L, and Boettger R, Social and cognitive strategies for coping with accountability: Conformity, complexity, and bolstering, Journal of Personality and Social Psychology, 1989, 57(4): 632–640.

    Article  Google Scholar 

  34. Cialdini R B and Trost M R, Social influence: Social norms, conformity and compliance, The Handbook of Social Psychology, McGraw-Hill, New York, NY, US, 1998, 151–192.

    Google Scholar 

  35. Allen V L and Wilder D A, Social comparison, self-evaluation, and conformity to the group, Social Comparison Processes: Theoretical and Empirical Perspectives, Hemisphere, Washington, DC, 1977, 187–208.

    Google Scholar 

  36. Cialdini R B and Goldstein N J, Social influence: compliance and conformity, Annual Review of Psychology, 2004, 55(1): 591–621.

    Article  Google Scholar 

  37. Yang B, Cheung W K, and Liu J, Community mining from signed social networks, IEEE Transactions on Knowledge and Data Engineering, 2007, 19(10): 1333–1348.

    Article  Google Scholar 

  38. Zhou J L, Li L B, and Zeng A, Random walk on signed networks, Physica A: Statistical Mechanics and Its Applications, 2018, 508: 558–566.

    Article  Google Scholar 

  39. Heider F, Attitudes and cognitive organization, Journal of Psychology, 1946, 21(1): 107–112.

    Article  Google Scholar 

  40. Traag V A and Bruggeman J, Community detection in networks with positive and negative links, Physical Review E, 2009, 80(2): 036115.

    Article  Google Scholar 

  41. Facchetti G, Iacono G, and Altafini C, Computing global structural balance in large-scale signed social networks, PNAS, 2011, 108(52): 20953–20958.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Systems Science, Beijing Normal University, Beijing, 100875, China

    Yue Gao, Ying Fan & Zengru Di

Authors
  1. Yue Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ying Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zengru Di
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ying Fan.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant Nos. 61573065 and 71731002.

This paper was recommended for publication by Editor JIA Yingmin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, Y., Fan, Y. & Di, Z. The Dynamics of Two-State Public Opinion Propagation On Signed Networks. J Syst Sci Complex 34, 251–264 (2021). https://doi.org/10.1007/s11424-020-9226-5

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11424-020-9226-5

Keywords

Search

Navigation