A Survey on Nonstrategic Models of Opinion Dynamics

The paper presents a survey on selected models of opinion dynamics. Both discrete (more precisely, binary) opinion models as well as continuous opinion models are discussed. We focus on frameworks that assume non-Bayesian updating of opinions. In the survey, a special attention is paid to modeling nonconformity (in particular, anticonformity) behavior. For the case of opinions represented by a binary variable, we recall the threshold model, the voter and q-voter models, the majority rule model, and the aggregation framework. For the case of continuous opinions, we present the DeGroot model and some of its variations, time-varying models, and bounded confidence models.

Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata

Hot events on Internet always attract many people who usually form one or several opinion camps through discussion. For the problem of polarization in Internet group opinions, we propose a new model based on Cellular Automata by considering neighbors, opinion leaders, and external influences. Simulation results show the following: (1) It is easy to form the polarization for both continuous opinions and discrete opinions when we only consider neighbors influence, and continuous opinions are more effective in speeding the polarization of group. (2) Coevolution mechanism takes more time to make the system stable, and the global coupling mechanism leads the system to consensus. (3) Opinion leaders play an important role in the development of consensus in Internet group opinions. However, both taking the opinion leaders as zealots and taking some randomly selected individuals as zealots are not conductive to the consensus. (4) Double opinion leaders with consistent opinions will accelerate the formation of group consensus, but the opposite opinions will lead to group polarization. (5) Only small external influences can change the evolutionary direction of Internet group opinions.

COMPARING EFFECTS OF CLUSTER-COUPLED PATTERNS ON OPINION DYNAMICS

Community structure is another important feature besides small-world and scale-free property of complex networks. Communities can be coupled through specific fixed links between nodes, or occasional encounter behavior. We introduce a model for opinion evolution with multiple cluster-coupled patterns, in which the interconnectivity denotes the coupled degree of communities by fixed links, and encounter frequency controls the coupled degree of communities by encounter behaviors. Considering the complicated cognitive system of people, the CODA (continuous opinions and discrete actions) update rules are used to mimic how people update their decisions after interacting with someone. It is shown that, large interconnectivity and encounter frequency both can promote consensus, reduce competition between communities and propagate some opinion successfully across the whole population. Encounter frequency is better than interconnectivity at facilitating the consensus of decisions. When the degree of social cohesion is same, small interconnectivity has better effects on lessening the competence between communities than small encounter frequency does, while large encounter frequency can make the greater degree of agreement across the whole populations than large interconnectivity can.

DEMPSTER–SHAFER EVIDENCE THEORY-BASED UPDATING RULE FOR CONTINUOUS OPINIONS AND DISCRETE ACTIONS

The opinion of an individual about a given problem is determined by the quantity and the degree of certainty of knowledge mastered by the individual. The knowledge and information from other individuals might bring some conflicts with the individual's internal knowledge, which would make the individual become uncertain about its opinion. Based on Dempster–Shafer (D–S) evidence theory, a new opinion updating rule is proposed for individuals to form their opinion as the process of reasoning from the internal or the external knowledge in real life. Many computer simulations are conducted under different situations. It is found that the common phenomena such as consensus, fragment opinions can be observed among the individuals on square lattices during the evolution of opinion, and that information is spread from the higher certainty to the lower certainty, and the influence of opinion leaders become weaken during the spread of information, and the range of influence is determined by the threshold of individual acceptance of uncertainty of information.

THE IMPORTANCE OF DISAGREEING: CONTRARIANS AND EXTREMISM IN THE CODA MODEL

In this paper, we study the effects of introducing contrarians in a model of Opinion Dynamics where the agents have internal continuous opinions, but exchange information only about a binary choice that is a function of their continuous opinion, the CODA model. We observe that the hung election scenario that arises when contrarians are introduced in discrete opinion models still happens. However, it is weaker and it should not be expected in every election. Finally, we also show that the introduction of contrarians make the tendency towards extremism of the original model weaker, indicating that the existence of agents that prefer to disagree might be an important aspect and help society to diminish extremist opinions.

CONTINUOUS OPINIONS AND DISCRETE ACTIONS IN OPINION DYNAMICS PROBLEMS

A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.