Emergence mechanisms of group consensus in social networks

Min WANG, Zi-Ke ZHANG

PDF(322 KB)
PDF(322 KB)
Front. Eng ›› 2024, Vol. 11 ›› Issue (2) : 362-368. DOI: 10.1007/s42524-023-0277-x
Comments
COMMENTS

Emergence mechanisms of group consensus in social networks

Author information +
History +

Abstract

Reaching consensus within larger social network groups has emerged as a pivotal concern in the digital age of connectivity. This article redefines group consensus as the emergence of collective intelligence resulting from self-organizing actions and interactions of individuals within a social network group. In our exploration of extant research on group consensus, we illuminate two frequently underestimated, yet noteworthy facets: Dynamism and emergence. In contrast to the conventional perspective of consensus as a mere outcome, we perceive it as an ongoing, dynamic process. This process encompasses self-organized communication and interaction among group members, collectively guiding the group towards cognitive convergence and viewpoint integration. Consequently, it is imperative to redirect our focus from the outcomes of group interactions to an examination of the relationships and processes underpinning consensus formation, thus elucidating the mechanisms responsible for the generation of group consensus. The amalgamation of cognitive contexts and accurate simplification of real-world scenarios for simulation and experimental analysis offers a pragmatic operational approach. This study contributes novel theoretical underpinnings and quantitative insights for establishing and sustaining group consensus within the realm of engineering management practices. Concurrently, it holds substantial importance for advancing the broader research landscape pertaining to social consensus.

Keywords

group consensus / social network / collective intelligence

Cite this article

Download citation ▾
Min WANG, Zi-Ke ZHANG. Emergence mechanisms of group consensus in social networks. Front. Eng, 2024, 11(2): 362‒368 https://doi.org/10.1007/s42524-023-0277-x

References

[1]
Alonso, S Herrera-Viedma, E Chiclana, F Herrera, F (2010). A web based consensus support system for group decision making problems and incomplete preferences. Information Sciences, 180( 23): 4477–4495
CrossRef Google scholar
[2]
Axelrod, R (1997). Advancing the art of simulation in the social sciences. Complexity, 3( 2): 16–22
CrossRef Google scholar
[3]
Bankes, S C (2002). Agent-based modeling: A revolution?. Proceedings of the National Academy of Sciences of the United States of America, 99( Suppl_3): 7199–7200
CrossRef Google scholar
[4]
Baronchelli, A (2018). The emergence of consensus: A primer. Royal Society Open Science, 5( 2): 172189
CrossRef Google scholar
[5]
BrownRPehrson S (2019). Group Processes: Dynamics Within and Between Groups. Hoboken, NJ: John Wiley & Sons
[6]
Bure, V M Parilina, E M Sedakov, A A (2017). Consensus in a social network with two principals. Automation and Remote Control, 78( 8): 1489–1499
CrossRef Google scholar
[7]
Cabrerizo, F J Ureña, R Pedrycz, W Herrera-Viedma, E (2014). Building consensus in group decision making with an allocation of information granularity. Fuzzy Sets and Systems, 255: 115–127
CrossRef Google scholar
[8]
Castellano, C Fortunato, S Loreto, V (2009). Statistical physics of social dynamics. Reviews of Modern Physics, 81( 2): 591–646
CrossRef Google scholar
[9]
CastellsM (1996). The Rise of the Network Society. Oxford: Blackwell
[10]
Chen, X Tsaparas, P Lijffijt, J de Bie, T (2021). Opinion dynamics with backfire effect and biased assimilation. PLoS One, 16( 9): e0256922
CrossRef Google scholar
[11]
Chiclana, F García, J T del, Moral M J Herrera-Viedma, E (2013). A statistical comparative study of different similarity measures of consensus in group decision making. Information Sciences, 221: 110–123
CrossRef Google scholar
[12]
Cinelli, M de Francisci Morales, G Galeazzi, A Quattrociocchi, W Starnini, M (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences of the United States of America, 118( 9): e2023301118
CrossRef Google scholar
[13]
Corning, P A (2002). The re-emergence of “emergence”: A venerable concept in search of a theory. Complexity, 7( 6): 18–30
CrossRef Google scholar
[14]
CrutchfieldJ P (1999). Is anything ever new? Considering emergence. In: Cowan G A, Pines D, Meltzer D, eds. Complexity: Metaphors, Models, and Reality. Cambridge, MA: Perseus Books, 515–537
[15]
de WolfTHolvoet T (2004). Emergence versus self-organisation: Different concepts but promising when combined. In: International Workshop on Engineering Self-Organising Applications. Berlin: Springer, 1–15
[16]
Degroot, M H (1974). Reaching a consensus. Journal of the American Statistical Association, 69( 345): 118–121
CrossRef Google scholar
[17]
Dong, Y Zha, Q Zhang, H Kou, G Fujita, H Chiclana, F Herrera-Viedma, E (2018). Consensus reaching in social network group decision making: Research paradigms and challenges. Knowledge-Based Systems, 162: 3–13
CrossRef Google scholar
[18]
Galton, F (1907). Vox Populi. Nature, 75( 1949): 450–451
CrossRef Google scholar
[19]
Geschke, D Lorenz, J Holtz, P (2019). The triple-filter bubble: Using agent-based modelling to test a meta-theoretical framework for the emergence of filter bubbles and echo chambers. British Journal of Social Psychology, 58( 1): 129–149
CrossRef Google scholar
[20]
GreenD GLeishman T GSadedinS (2007). The emergence of social consensus in Boolean networks. In: IEEE Symposium on Artificial Life. Honolulu, HI: IEEE, 402–408
[21]
Hassani, H Razavi-Far, R Saif, M Chiclana, F Krejcar, O Herrera-Viedma, E (2022). Classical dynamic consensus and opinion dynamics models: A survey of recent trends and methodologies. Information Fusion, 88: 22–40
CrossRef Google scholar
[22]
Herrera-Viedma, E Alonso, S Chiclana, F Herrera, F (2007). A consensus model for group decision making with incomplete fuzzy preference relations. IEEE Transactions on Fuzzy Systems, 15( 5): 863–877
CrossRef Google scholar
[23]
Herrera-Viedma, E Cabrerizo, F J Kacprzyk, J Pedrycz, W (2014). A review of soft consensus models in a fuzzy environment. Information Fusion, 17: 4–13
CrossRef Google scholar
[24]
Janis, I L (2008). Groupthink. IEEE Engineering Management Review, 36( 1): 36
CrossRef Google scholar
[25]
KellyK (2009). Out of Control: The New Biology of Machines, Social Systems, and the Economic World. Boston, MA: Addison-Wesley Longman Publishing Co., Inc.
[26]
Klapp, O E (1957). The concept of consensus and its importance. Sociology and Social Research, 41( 5): 336–342
[27]
Krause, J Ruxton, G D Krause, S (2010). Swarm intelligence in animals and humans. Trends in Ecology & Evolution, 25( 1): 28–34
CrossRef Google scholar
[28]
Le BonG (2002). The Crowd: A Study of the Popular Mind. North Chelmsford, MI: Courier Corporation
[29]
LévyP (1997). Collective Intelligence: Mankind’s Emerging World in Cyberspace (trans. Bononno R). Cambridge, MA: Perseus Books
[30]
Li, L Scaglione, A Swami, A Zhao, Q (2013). Consensus, polarization and clustering of opinions in social networks. IEEE Journal on Selected Areas in Communications, 31( 6): 1072–1083
CrossRef Google scholar
[31]
Liu, Y Liang, H Gao, L Guo, Z (2021). Optimizing consensus reaching in the hybrid opinion dynamics in a social network. Information Fusion, 72: 89–99
CrossRef Google scholar
[32]
Noorazar, H (2020). Recent advances in opinion propagation dynamics: A 2020 survey. European Physical Journal Plus, 135( 6): 521
CrossRef Google scholar
[33]
Oppenheimer, M O’Neill, B C Webster, M Agrawala, S (2007). The limits of consensus. Science, 317( 5844): 1505–1506
CrossRef Google scholar
[34]
PageS E (2007). The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies. Princeton, NJ: Princeton University Press
[35]
SalminenJ (2012). Collective intelligence in humans: A literature review. arXiv preprint, arXiv:1204.3401
[36]
Scheff, T J (1967). Toward a sociological model of consensus. American Sociological Review, 32( 1): 32–46
CrossRef Google scholar
[37]
ShirkyC (2008). Here Comes Everybody: The Power of Organizing Without Organizations. London: Penguin Books
[38]
Sobkowicz, P (2023). Social depolarization and diversity of opinions: Unified ABM framework. Entropy, 25( 4): 568
CrossRef Google scholar
[39]
Song, H Boomgaarden, H G (2017). Dynamic spirals put to test: An agent-based model of reinforcing spirals between selective exposure, interpersonal networks, and attitude polarization. Journal of Communication, 67( 2): 256–281
CrossRef Google scholar
[40]
SurowieckiJ (2004). The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. New York, NY: Doubleday
[41]
van Dolder, D van den Assem, M J (2018). The wisdom of the inner crowd in three large natural experiments. Nature Human Behaviour, 2( 1): 21–26
CrossRef Google scholar
[42]
Weschsler, D (1971). Concept of collective intelligence. American Psychologist, 26( 10): 904–907
CrossRef Google scholar
[43]
Woolley, A W Aggarwal, I Malone, T W (2015). Collective intelligence and group performance. Current Directions in Psychological Science, 24( 6): 420–424
CrossRef Google scholar
[44]
Woolley, A W Chabris, C F Pentland, A Hashmi, N Malone, T W (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330( 6004): 686–688
CrossRef Google scholar
[45]
Wu, J Chiclana, F Herrera-Viedma, E (2015). Trust based consensus model for social network in an incomplete linguistic information context. Applied Soft Computing, 35: 827–839
CrossRef Google scholar
[46]
Zhang, H Dong, Y Xiao, J Chiclana, F Herrera-Viedma, E (2021). Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts. Reliability Engineering & System Safety, 208: 107425
CrossRef Google scholar
[47]
Zhou, Q Wu, Z Altalhi, A H Herrera, F (2020). A two-step communication opinion dynamics model with self-persistence and influence index for social networks based on the Degroot model. Information Sciences, 519: 363–381
CrossRef Google scholar
[48]
Zollman, K J (2012). Social network structure and the achievement of consensus. Politics, Philosophy & Economics, 11( 1): 26–44
CrossRef Google scholar

Competing Interests

The authors declare that they have no competing interests.

RIGHTS & PERMISSIONS

2023 Higher Education Press
AI Summary AI Mindmap
PDF(322 KB)

Accesses

Citations

Detail

Sections
Recommended

/