ArticlePloS one2019
Opinion limits study for the multi-selection bounded confidence model.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed, 2 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this work, we study the opinion limit states for a generalized bounded confidence agent-based opinion model. Agents can select multiple opinions in the network, and the confidence bound is considered on the distance between the average of the selected opinions and agent opinion itself. The number of selection agents for a certain agent, which is also called the selection number, means the agent opinion interaction degree. It is known that when the confidence bound is large sufficiently, opinions reach consensus almost surely. We mainly study the opinion consensus and the opinion polarization when the confidence bound is small sufficiently. Firstly, we provide and prove the upper and lower bounds for the opinion consensus probability of this bound confidence model. It shows that the opinion consensus probability almost always decreases as the confidence bound decreases. Secondly, the opinion consensus probability is larger than the one for the opinion evolution of the Deffuant-Weisbuch model. Finally, we demonstrate the ultimate probability distribution of one agent opinion and compare it with the gossip form and the general bounded confidence form, and demonstrate how the opinion polarization probabilities evolve as the selection number changes. Specially, different from other studies, we find that the opinion polarization would happen more easily if the opinion interaction degree is strengthened. In a sum, the multiple selection mechanism will increase the opinion consensus probability and the opinion polarization probability, respectively, comparing to the single selection mechanism.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.