Dynamical model for competing opinions

Abstract

We propose an opinion model based on agents located at the vertices of a regular lattice. Each agent has an independent opinion (among an arbitrary, but fixed, number of choices) and its own degree of conviction. The latter changes every time two agents which have different opinions interact with each other. The dynamics leads to size distributions of clusters (made up of agents which have the same opinion and are located at contiguous spatial positions) which follow a power law, as long as the range of the interaction between the agents is not too short; i.e., the system self-organizes into a critical state. Short range interactions lead to an exponential cutoff in the size distribution and to spatial correlations which cause agents which have the same opinion to be closely grouped. When the diversity of opinions is restricted to two, a nonconsensus dynamic is observed, with unequal population fractions, whereas consensus is reached if the agents are also allowed to interact with those located far from them. The individual agents' convictions, the preestablished interaction range, and the locality of the interaction between a pair of agents (their neighborhood has no effect on the interaction) are the main characteristics which distinguish our model from previous ones.

The Undecided Have the Key: Interaction-Driven Opinion Dynamics in a Three State Model

“…The individuals can have either one of the two opposing views, and also be undecided. After random encounters, agents may increase or decrease their persuasions depending on the opinion of the opponent [ 32 , 33 ]. These social interactions produce cumulative changes that can eventually lead to the change of opinion: a shift in opinion occurs when the persuasion exceeds a certain threshold.…”

Macroscopic and microscopic perspectives for adoption of technologies in the USA

“…Perhaps using an ecosystem model of innovations and their survival times or a mix of the present model with the model presented in “Dynamical model for competing opinions” (Ref. [ 27 ]). Other databases should also be used, with data on the consumption of different types of products and survival times, if available.…”

Voter model with arbitrary degree dependence: clout, confidence and irreversibility

“…This is longer than the consensus time given by (31), due to the extra term in the numerator that stems from the confidence of nodes.…”

“…Similarly, for the denominator of (31) we obtain k 2 f (k) 2 ∼ N . Inserting these limits into (31), we arrive at…”

“…In [29], time-dependent transition rates are considered through a noise-reduction scheme. In [30], [31], nodes have heterogeneous conviction (or persuasion). In [32]- [34] an 'adaptive' network is envisaged, where links whose incident nodes are of opposing states are rewired so that the new link has two agreeing nodes at its ends.…”