Evidence map›Paper›PMID 36832551›Full record

ArticleEntropy (Basel, Switzerland)2023

Opinion Dynamics Systems on Barabási-Albert Networks: Biswas-Chatterjee-Sen Model.

David S M Alencar, Tayroni F A Alves, Gladstone A Alves, Antonio Macedo-Filho, Ronan S Ferreira, F Welington S Lima, Joao A Plascak

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Entropy (Basel, Switzerland), 2023. 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. Deep Learning of the Biswas-Chatterjee-Sen Model.Entropy (Basel, Switzerland) · 2025
    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

7 authors.

David S M AlencarDietrich Stauffer Computational Physics Lab, Departamento de Física, Universidade Federal do Piauí, Teresina 64049-550, PI, Brazil.
Tayroni F A AlvesDietrich Stauffer Computational Physics Lab, Departamento de Física, Universidade Federal do Piauí, Teresina 64049-550, PI, Brazil.
Gladstone A AlvesDepartamento de Física, Universidade Estadual do Piauí, Teresina 64002-150, PI, Brazil.
Antonio Macedo-FilhoDepartamento de Física, Universidade Estadual do Piauí, Teresina 64002-150, PI, Brazil.
Ronan S FerreiraDepartamento de Ciências Exatas e Aplicadas, Universidade Federal de Ouro Preto, João Monlevade 35931-008, MG, Brazil.ORCID 0000-0002-7623-1361
F Welington S LimaDietrich Stauffer Computational Physics Lab, Departamento de Física, Universidade Federal do Piauí, Teresina 64049-550, PI, Brazil.ORCID 0000-0003-0895-4186
Joao A PlascakDepartamento de Física, Centro de Ciências Exatas e da Natureza, CCEN, Universidade Federal da Paraíba, Cidade Universitária, João Pessoa 58051-970, PB, Brazil.ORCID 0000-0002-5135-1674

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A discrete version of opinion dynamics systems, based on the Biswas-Chatterjee-Sen (BChS) model, has been studied on Barabási-Albert networks (BANs). In this model, depending on a pre-defined noise parameter, the mutual affinities can assign either positive or negative values. By employing extensive computer simulations with Monte Carlo algorithms, allied with finite-size scaling hypothesis, second-order phase transitions have been observed. The corresponding critical noise and the usual ratios of the critical exponents have been computed, in the thermodynamic limit, as a function of the average connectivity. The effective dimension of the system, defined through a hyper-scaling relation, is close to one, and it turns out to be connectivity-independent. The results also indicate that the discrete BChS model has a similar behavior on

Indexed as

Biswas–Chatterjee–Sen modelfinite-size-scaling hypothesisopinion dynamics systemssecond-order phase transitionsuniversality class

Identifiers

PMID36832551
PMCPMC9955105

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.