Evidence map›Paper›PMID 37420373›Full record

ArticleEntropy (Basel, Switzerland)2022

Feedback Loops in Opinion Dynamics of Agent-Based Models with Multiplicative Noise.

Nataša Djurdjevac Conrad, Jonas Köppl, Ana Djurdjevac

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nataša Djurdjevac ConradZuse Institute Berlin, 14195 Berlin, Germany.ORCID 0000-0001-8422-4930
Jonas KöpplZuse Institute Berlin, 14195 Berlin, Germany.
Ana DjurdjevacDepartment of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany.ORCID 0000-0002-8122-7164

Funding

Deutsche Forschungsgemeinschaft CRC 1114 "Scaling Cascades in Complex Systems", Project Number 235221301, Project C10
6 · The paper itself

Abstract

We introduce an agent-based model for co-evolving opinions and social dynamics, under the influence of multiplicative noise. In this model, every agent is characterized by a position in a social space and a continuous opinion state variable. Agents' movements are governed by the positions and opinions of other agents and similarly, the opinion dynamics are influenced by agents' spatial proximity and their opinion similarity. Using numerical simulations and formal analyses, we study this feedback loop between opinion dynamics and the mobility of agents in a social space. We investigate the behaviour of this ABM in different regimes and explore the influence of various factors on the appearance of emerging phenomena such as group formation and opinion consensus. We study the empirical distribution, and, in the limit of infinite number of agents, we derive a corresponding reduced model given by a partial differential equation (PDE). Finally, using numerical examples, we show that a resulting PDE model is a good approximation of the original ABM.

Indexed as

agent-based modelingempirical distributionfeedback loopgroup formationmean-field limitmultiplicative noiseopinion dynamicsstochastic partial differential equations

Identifiers

PMID37420373
PMCPMC9601133

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.