Deep MARL models opinion dynamics at scale, showing high conformity reduces collective accuracy in large networks while sometimes improving it in small ones.
Opinion dynamics: Statistical physics and beyond
13 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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Pith papers citing it
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external citations · OpenAlex
abstract
Opinion dynamics, the study of how individual beliefs and collective public opinion evolve, is a fertile domain for applying statistical physics to complex social phenomena. Like physical systems, societies exhibit macroscopic regularities from localized interactions, leading to outcomes such as consensus or fragmentation. This field has grown significantly, attracting interdisciplinary methods and driven by a surge in large-scale behavioral data. This review covers its rapid progress, bridging the literature dispersion. We begin with essential concepts and definitions, encompassing the nature of opinions, microscopic and macroscopic dynamics. This foundation leads to an overview of empirical research, from lab experiments to large-scale data analysis, which informs and validates models of opinion dynamics. We then present individual-based models, categorized by their macroscopic phenomena (e.g., consensus, polarization, echo chambers) and microscopic mechanisms (e.g., homophily, assimilation). Furthermore, the review covers common analytical and computational tools, including stochastic processes, treatments, simulations, and optimization. Finally, we explore emerging frontiers, such as connecting empirical data to models and using AI agents as testbeds for novel social phenomena. By systematizing terminology and emphasizing analogies with traditional physics, this review aims to consolidate knowledge, provide a robust theoretical foundation, and shape future research in opinion dynamics.
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LLM multi-agent systems on lattices show bias-driven order-disorder crossovers instead of true phase transitions, with extracted effective couplings and fields serving as model-specific fingerprints.
First systematic comparison of DA and LBI on the Bounded-Confidence ABM finds LBI superior for recovering latent agent-level opinions and individual forecasts, with comparable aggregate performance.
In the partisan voter model on uncorrelated networks, partisan bias leaves the stationary total density of active links unchanged (ρst=ξ), while preference-based homophily shifts it and creates distinct ordering regimes.
The authors extend the DW opinion dynamics model with adaptive edge weights on networks, prove convergence and effective-graph properties, and simulate that adaptive weights speed convergence on dense networks but slow it on sparse ones for small confidence bounds.
Intermediate hyperedge nestedness minimizes the simplicial contagion outbreak threshold and intermediate social reinforcement minimizes the prefactor of logarithmic consensus time in hypergraph models due to competition between simple and higher-order processes.
When transition rates of two competing mechanisms sum equally, annealed and quenched binary-choice dynamics coincide, heterogeneity reduces to the mean preference, and oscillations are impossible.
Epidemic models on multigraphs and simple graphs with identical degree sequences differ only when activity persists exponentially long on star-like hubs.
A framework uses stance detection, linear dimensionality reduction, and neural potential landscapes to recover a 3D stance space explaining 45% variance and to visualize large-scale shifts across platforms and years.
Ratio-dependent contrarian activation in groups of three extends the Galam model to allow strategies that bias outcomes toward the initial majority or enforce random fifty-fifty results.
A generalized mean-field resource model on the simplex has a unique explicit equilibrium to which every trajectory converges monotonically, with parameter regimes for uniform versus aggregated distributions.
Extension of the DW bounded-confidence model with two opposing media sources shows drifting of opinion clusters toward one media source, demonstrated numerically and analytically.
Pedagogical lecture notes derive standard RMT laws with the cavity method, illustrate applications, and catalogue advanced analytical techniques for disordered systems.
citing papers explorer
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Modelling Opinion Dynamics at Scale with Deep MARL
Deep MARL models opinion dynamics at scale, showing high conformity reduces collective accuracy in large networks while sometimes improving it in small ones.
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Collective Alignment in LLM Multi-Agent Systems: Disentangling Bias from Cooperation via Statistical Physics
LLM multi-agent systems on lattices show bias-driven order-disorder crossovers instead of true phase transitions, with extracted effective couplings and fields serving as model-specific fingerprints.
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Comparing Data Assimilation and Likelihood-Based Inference on Latent State Estimation in Agent-Based Models
First systematic comparison of DA and LBI on the Bounded-Confidence ABM finds LBI superior for recovering latent agent-level opinions and individual forecasts, with comparable aggregate performance.
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Partisan voter model on complex networks: Dynamics of local ordering
In the partisan voter model on uncorrelated networks, partisan bias leaves the stationary total density of active links unchanged (ρst=ξ), while preference-based homophily shifts it and creates distinct ordering regimes.
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A Bounded-Confidence Model of Opinion Dynamics with Adaptive Interaction Probabilities
The authors extend the DW opinion dynamics model with adaptive edge weights on networks, prove convergence and effective-graph properties, and simulate that adaptive weights speed convergence on dense networks but slow it on sparse ones for small confidence bounds.
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Optimality in group-driven social dynamics on hypergraphs
Intermediate hyperedge nestedness minimizes the simplicial contagion outbreak threshold and intermediate social reinforcement minimizes the prefactor of logarithmic consensus time in hypergraph models due to competition between simple and higher-order processes.
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Unified Framework for Binary-Choice Dynamics: Analysis and Applications
When transition rates of two competing mechanisms sum equally, annealed and quenched binary-choice dynamics coincide, heterogeneity reduces to the mean preference, and oscillations are impossible.
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Epidemic spreading on multigraphs
Epidemic models on multigraphs and simple graphs with identical degree sequences differ only when activity persists exponentially long on star-like hubs.
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Mapping the Winds of Stance Dynamics using Potential Landscape Models
A framework uses stance detection, linear dimensionality reduction, and neural potential landscapes to recover a 3D stance space explaining 45% variance and to visualize large-scale shifts across platforms and years.
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Ratio-Dependent Contrarian Activation in Opinion Dynamics
Ratio-dependent contrarian activation in groups of three extends the Galam model to allow strategies that bias outcomes toward the initial majority or enforce random fifty-fifty results.
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Mean-field dynamics of attractive resource interaction: From uniform to aggregated states
A generalized mean-field resource model on the simplex has a unique explicit equilibrium to which every trajectory converges monotonically, with parameter regimes for uniform versus aggregated distributions.
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Drift Behavior in a Bounded-Confidence Opinion Model with Media Influence
Extension of the DW bounded-confidence model with two opposing media sources shows drifting of opinion clusters toward one media source, demonstrated numerically and analytically.
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Lecture notes on random matrix theory: the results, the applications, and the analytical tools
Pedagogical lecture notes derive standard RMT laws with the cavity method, illustrate applications, and catalogue advanced analytical techniques for disordered systems.