No Access

Prediction of collective opinion in consensus formation

Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China

Search for more papers by this author

Jianguo Liu

Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China

Corresponding author.

Search for more papers by this author

Xue Pan

Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China

Search for more papers by this author

Wen-Jun Song

Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China

Search for more papers by this author

, and

Xu-Dong Li

Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China

Search for more papers by this author

https://doi.org/10.1142/S0129183114500028Cited by:8 (Source: Crossref)

Abstract

In the consensus formation dynamics, the effect of leaders and interventions have been widely studied for it has many applications such as in politics and commerce. However, the problem is how to know if it is necessary for one to make an intervention. In this paper, we theoretically propose a method for predicting the tendency and final state of collective opinion. By giving each agent a conviction c_i which measures the ability to insist on his opinion, we present an opinion formation model in which agents with high convictions naturally show up properties of the opinion leaders. Results reveal that, although each agent initially gets an opinion evenly distributed in the range [-1, 1], the collective opinion of the steady-state may deviate to the positive or negative direction because of the initial bias of the leaders' opinions. We further get the correlation coefficient of the linear relationship between the collective opinion and the initial bias according to both the experimental and theoretical analysis. Thus, we could predict the final state at the very beginning of the dynamic only if we get the opinions of a small portion of the population. The prediction would afford us more time and opportunities to make reactions and interventions.

Keywords:

PACS: 89.75.Hc, 89.65.-s, 87.23.Ge

You currently do not have access to the full text article.
Recommend the journal to your library today!

References

D. J. Watts and P. S. Dodds, J. Consum. Res. 34, 441 (2007), DOI: 10.1086/518527. Web of Science, Google Scholar
C. Castellano, S. Fortunato and V. Loreto, Rev. Mod. Phys. 81, 000591 (2009), DOI: 10.1103/RevModPhys.81.591. Web of Science, ADS, Google Scholar
C. Nardini, B. Kozma and A. Barrat, Phys. Rev. Lett. 100, 158701 (2008), DOI: 10.1103/PhysRevLett.100.158701. Web of Science, ADS, Google Scholar
V. Schwammleet al., Phys. Rev. E 75, 066108 (2007). Web of Science, Google Scholar
R. Wang and Q. A. Wang, Phys. Rev. E 84, 036108 (2011), DOI: 10.1103/PhysRevE.84.036108. Web of Science, Google Scholar
M. Karsaiet al., Phys. Rev. E 83, 025102 (2011), DOI: 10.1103/PhysRevE.83.025102. Web of Science, Google Scholar
P. G. Lind and H. J. Herrmann, New J. Phys. 9, 228 (2007), DOI: 10.1088/1367-2630/9/7/228. Web of Science, Google Scholar
I. D. Couzinet al., Nature 433, 513 (2005), DOI: 10.1038/nature03236. Web of Science, ADS, Google Scholar
B. Duringet al., Proc. R. Soc. London, Ser. A 465, 3687 (2009), DOI: 10.1098/rspa.2009.0239. Web of Science, ADS, Google Scholar
B. During, SIAM News 44, 1 (2011). Web of Science, Google Scholar
N. Boccara, Int. J. Mod. Phys. C 19, 93 (2008), DOI: 10.1142/S0129183108011954. Link, Web of Science, ADS, Google Scholar
P. Sobkowicz, Int. J. Mod. Phys. C 21, 839 (2010), DOI: 10.1142/S0129183110015518. Link, Web of Science, ADS, Google Scholar
C. M. Bordogna and E. V. Albano, Phys. Rev. E 76, 061125 (2007), DOI: 10.1103/PhysRevE.76.061125. Web of Science, Google Scholar
J. A. Holysta, K. Kacperskia and F. Schweitzer, Physica A 285, 199 (2000). ADS, Google Scholar
B. Latane, Am. Psychol. 36, 343 (1981). Web of Science, Google Scholar
N. Crokidakis and C. Anteneodo, Phys. Rev. E 86, 061127 (2012), DOI: 10.1103/PhysRevE.86.061127. Web of Science, Google Scholar
R. A. Holley and T. M. Liggett, Ann. Probab. 3, 643 (1975), DOI: 10.1214/aop/1176996306. Web of Science, Google Scholar
K. Sznajd-Weron and J. Sznajd, Int. J. Mod. Phys. C 11, 1157 (2000), DOI: 10.1142/S0129183100000936. Link, Web of Science, ADS, Google Scholar
R. Hegselmann and U. Krause, J. Artif. Soc. Soc. Simul. 5, 2 (2002). Google Scholar
J.-G. Liu, Z. X. Wu and F. Wang, Int. J. Mod. Phys. C 18, 1087 (2007), DOI: 10.1142/S0129183107011145. Link, Web of Science, Google Scholar
V. Sood and S. Redner, Phys. Rev. Lett. 94, 178701 (2005), DOI: 10.1103/PhysRevLett.94.178701. Web of Science, ADS, Google Scholar
Q. Guoet al., Chin. Phys. Lett. 25, 773 (2008). Web of Science, ADS, Google Scholar
M. C. Gonzalez, A. O. Sousa and H. J. Herrmann, Int. J. Mod. Phys. C 15, 45 (2004). Link, Web of Science, ADS, Google Scholar
M. Lallouacheet al., Phys. Rev. E 82, 056112 (2010), DOI: 10.1103/PhysRevE.82.056112. Web of Science, Google Scholar
A. T. Bernardeset al., Int. J. Mod. Phys. C 12, 159 (2001), DOI: 10.1142/S0129183101001584. Link, Web of Science, ADS, Google Scholar
G. Deffuantet al., Adv. Comp. Syst. 3, 87 (2000), DOI: 10.1142/S0219525900000078. Link, Google Scholar
B. Kozma and A. Barrat, Phys. Rev. E 77, 016102 (2008), DOI: 10.1103/PhysRevE.77.016102. Web of Science, Google Scholar
G. Iniguezet al., Phys. Rev. E 80, 066119 (2009). Web of Science, Google Scholar