Pith. sign in

REVIEW 5 cited by

Emergence of echo chambers in a noisy adaptive voter model

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2409.12933 v2 pith:XUYG5LWG submitted 2024-09-19 physics.soc-ph nlin.AO

André Martin Timpanaro This is my paper
classification physics.soc-phnlin.AO
keywords networkopinionadaptiveagentsbeliefblockingchambersecho
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Belief perseverance is the widely documented tendency of holding to a belief, even in the presence of contradicting evidence. In online environments, this tendency leads to heated arguments with users ``blocking'' each other. Introducing this element to opinion modelling in a social network, leads to an adaptive network where agents tend to connect preferentially to like-minded peers. In this work we study how this type of dynamics behaves in the voter model with the addition of a noise that makes agents change opinion at random. As the intensity of the noise and the propensity of users blocking each other is changed, we observe a transition between 2 phases. One in which there is only one community in the whole network and another where communities arise and in each of then there is a very clear majority opinion, mimicking the phenomenon of echo chambers. These results are obtained with simulations and with a mean-field theory.

Discussion (0). Sign in to comment.

Forward citations

Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. A model of opinion dynamics evolving via a preferential attachment mechanism involving multiple extractions

    math.PR 2026-08 conditional novelty 6.0 of 10

    For a two-opinion preferential-attachment network with multiple sampling and general reinforcement, the normalized opinion count, influence capital and activity converge almost surely to invariant sets of a mean-field...

  2. A Bounded-Confidence Model of Opinion Dynamics with Adaptive Interaction Probabilities

    physics.soc-ph 2026-05 unverdicted novelty 6.0 of 10

    An adaptive edge-weighted version of the DW opinion dynamics model is introduced with proven convergence properties and network-dependent effects on convergence time shown via simulations.

  3. A Bounded-Confidence Model of Opinion Dynamics with Adaptive Interaction Probabilities

    physics.soc-ph 2026-05 unverdicted novelty 6.0 of 10

    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 slo...

  4. Spontaneous Symmetry Breaking, Group Decision Making and Beyond 2. Distorted Polarization and Vulnerability

    physics.soc-ph 2025-09 conditional novelty 4.0 of 10

    In a zero-temperature Ising-like model of opinion dynamics, a single well-placed local field, or two opposed fields at the right sites, can override the random spontaneous consensus and force a predetermined majority.

  5. Opinion dynamics: Statistical physics and beyond

    physics.soc-ph 2025-07 unverdicted novelty 2.0 of 10

    A review synthesizing opinion dynamics research, categorizing models by macroscopic outcomes and microscopic mechanisms while connecting to empirical data and emerging AI tools.

Pith tools