Related Experiment Video
Updated: Jul 23, 2025
08:38
A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
Published on: November 21, 2019
7.7K
Stochastic thermodynamics of opinion dynamics models
Tânia Tomé1, Carlos E Fiore1, Mário J de Oliveira1
1Universidade de São Paulo, Instituto de Física, Rua do Matão, 1371, 05508-090 São Paulo, SP, Brazil.
Physical Review. E
|July 19, 2023
Summary
We introduce a new framework for understanding opinion dynamics using nonequilibrium thermodynamics. This approach reveals how heat fluxes and entropy production drive opinion changes in communities.
Area of Science:
- Statistical Mechanics
- Sociophysics
- Complex Systems
Background:
- Opinion formation and dissemination are complex social phenomena.
- Existing models often lack a rigorous thermodynamic foundation.
Purpose of the Study:
- To develop a nonequilibrium thermodynamic framework for opinion dynamics.
- To analyze opinion formation and dissemination using principles of stochastic thermodynamics.
Main Methods:
- Decomposing opinion model transition rates into contact with heat reservoirs at different temperatures.
- Postulating an energy function for the opinion system.
- Applying the framework to generic-vote and majority-vote models on lattices.
Main Results:
- Demonstrated the presence of heat fluxes and entropy production even in stationary states.
- Linked heat fluxes to entropy production, a key indicator of nonequilibrium states.
- Calculated fluxes and entropy production rates using numerical simulations and pair approximation.
Conclusions:
- The developed framework provides a novel perspective on opinion dynamics through nonequilibrium thermodynamics.
- This approach offers a quantitative method to study the fundamental processes driving opinion changes in communities.
Related Concept Videos
01:14The Second Law of Thermodynamics
5.4K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
5.4K
01:20Entropy and the Second Law of Thermodynamics
2.9K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
The relation between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
2.9K
02:49Second Law of Thermodynamics
24.0K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic...
24.0K
02:39Entropy
30.4K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
30.4K
01:10Entropy Change in Reversible Processes
2.6K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.6K
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
64
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
64