People like to communicate with others who have similar opinions in daily life. “Open” individuals are willing to accept peers’ opinions, whereas “conservative” individuals are more closed to others’ opinions. Based on this reality, an opinion dynamic model is proposed with a time-varying trust threshold related to the node degree, which refers to the number of individuals that can be communicated directly. Similar opinions within the trust thresholds at the beginning will eventually form a consensus opinion. Individuals who have common neighbors converge to consensus faster than ones who have no common neighbors. The network size impacts the convergent speed of the opinion cluster and the trust threshold cluster. Individuals in small groups are more stressed than in large ones when they try to insist their opinions. A group with half of the individuals categorized as doubting and the other half categorized as trusting exhibits consistent confidence but experiences difficulty in reaching a consensus: “harmony but difference” may be a criterion for unifying a group.
MoussaïdMKämmerJEAnalytisPPet al. Social influence and the collective dynamics of opinion formation. Plos One2013; 8: e78433.
2.
LataneB.The psychology of social impact. Am Psychol1981; 36: 343–356.
3.
BonGL.Psychologie des foules. New York: Viking Press, 1960.
4.
ConradtLRoperTJ.Group decision-making in animals. Nature2003; 421: 155-158.
5.
DyerJRGJohanssonAHelbingDet al. Leadership, consensus decision making and collective behaviour in humans. Philos Trans R Soc B Biol Sci2009; 364: 781.
6.
CurşeuPLKrehelOEversJHet al. Cognitive distance, absorptive capacity and group rationality: a simulation study. Plos One2014; 9: e109359.
7.
Williams WoolleyAChabrisCFPentlandAet al. Evidence for a collective intelligence factor in the performance of human groups. Science2010; 330: 686-688.
8.
MillerNGarnierSHartnettATet al. Both information and social cohesion determine collective decisions in animal groups. Proc Natl Acad Sci USA2013; 110: 5263.
9.
CastellanoCFortunatoSLoretoV.Statistical physics of social dynamics. Rev Mod Phys2009; 81: 591-646.
10.
JainSMukandS.Public opinion and the dynamics of reform. Discussion Papers2003.
11.
MunroePT.Social influence network theory: a sociological examination of small group dynamics. Contemp Soc2013; 42: 560-562.
12.
SobkowiczP.Modelling opinion formation with physics tools: call for closer link with reality. J Artif Soc Soc Simulat2009; 12: 11.
13.
LorenzJRauhutHSchweitzerFet al. How social influence can undermine the wisdom of crowd effect. Proc Natl Acad Sci USA2011; 108: 9020-9025.
14.
KaoABCouzinID.Decision accuracy in complex environments is often maximized by small group sizes. Proc R Soc Lond B Biol Sci2014; 281: 437-446.
15.
GlauberRJ.Time-dependent statistics of the Ising model. J Math Phys1963; 4: 294–307.
16.
CliffordPSudburyA.A model for spatial conflict. Biometrika1973; 60: 581–588.
17.
GalamS.Minority opinion spreading in random geometry. Eur Phys J B2002; 25: 403–406.
18.
NowakASzamrejJLataneB.From private attitude to public-opinion: a dynamic theory of social impact. Psychol Rev1990; 97: 362–376.
19.
Sznajd-WeronKSznajdJ.Opinion evolution in closed community. Int J Mod Phys C2000; 11: 1157–1165.
20.
DegrootMH.Reaching a consensus. J Am Stat Assoc1974; 69: 118–121.
21.
DeffuantGNeauDAmblardF.Mixing beliefs among interacting agents. Adv Complex Syst2000; 3: 87-98.
22.
HegselmannRKrauseU.Opinion dynamics and bounded confidence models, analysis and simulation. J Artif Soc Soc Simulat2002; 5: 2.
23.
LiuQWangX.Social learning in networks with time-varying topologies. Asian J Contr2015; 16: 1342–1349.
24.
LiuQFangAWangLet al. Social learning with time-varying weights. J Syst Sci Complex2014; 27: 581-593.
25.
HanXPZhaoZDHadzibeganovicTet al. Epidemic spreading on hierarchical geographical networks with mobile agents. Commun Nonlin Sci Numer Simulat2014; 19: 1301–1312.
26.
ZhangYLiuQWangZet al. On the opinion formation of mobile agents with memory. Phys A Stat Mech Appl2018; 492: 438-445.
27.
JingHMingLLeiG.Soft control on collective behavior of a group of autonomous agents by a shill agent. J Syst Sci Complex2006; 19: 54-62.
28.
ZhangYLiuQZhangS.Opinion formation with time-varying bounded confidence. Plos One2017; 12: e0172982.
29.
FuGZhangW.Opinion formation and bi-polarization with biased assimilation and homophily. Phys A Stat Mech Appl2016; 444: 700-712.
30.
XuBGaoLZhangYet al. Leader-following consensus stability of discrete-time linear multiagent systems with observer-based protocols. Abstr Appl Anal2013; 2013: 1140–1174.
31.
DingZLiangHDongYet al. An opinion control rule with minimum adjustments to support the consensus reaching in bounded confidence model. Proc Comput Sci2016; 91: 617-624.
32.
LiuZMaJZengYet al. On the control of opinion dynamics in social networks. Phys A Stat Mech Appl2014; 409: 183–198.
33.
MaJZhengYWuBet al. Equilibrium topology of multi-agent systems with two leaders. Automatica2016; 73: 200–206.
34.
ZhengYMaJWangL.Consensus of hybrid multi-agent systems. IEEE Trans Neur Network Learn Syst2017; PP: 1-7.
35.
ZhengYWangL.Consensus of switched multiagent systems. Int J Contr2016; 90: 1113–1122.
36.
WeiBXiaoFDaiM.Edge event-triggered synchronization in networks of coupled harmonic oscillators. IEEE Trans Cybern2017; 47: 4162-4168.
37.
WeiBLiuJWeiDet al. Weighted k-shell decomposition for complex networks based on potential edge weights. Phys A Stat Mech Appl2015; 420: 277–283.
38.
SmithAE. Swarm intelligence: from natural to artificial systems. IEEE Transactions on Evolutionary Computation2002; 4(2):192–193.
