Opinion evolution in open community

Pan, Qiuhui; Qin, Yao; Xu, Yiqun; Tong, Mengfei; He, Mingfeng

doi:10.1142/s0129183117500036

Cited by 9 publications

(9 citation statements)

References 22 publications

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“…Although the use of continuous models [4][5][6][7][8][9][10][11][12][13] enables the modelling of broader social contexts, there are many social scenarios in which the possible choices are limited and thus can be modeled by discrete variables [14][15][16][17][18][19][20] as was done in this work. Apart from this, discrete models have the advantage of allowing a better understanding of the underlying mechanism behind the macroscopic outcomes through an analytical treatment.…”

Section: Introductionmentioning

confidence: 99%

Three-state opinion dynamics in modular networks

2019

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In this work we study the opinion evolution in a community-based population with intergroup interactions. We address two issues. First, we consider that such intergroup interactions can be negative with some probability p. We develop a coupled mean-field approximation that still preserves the community structure and it is able to capture the richness of the results arising from our Monte Carlo simulations: continuous and discontinuous order-disorder transitions as well as nonmonotonic ordering for an intermediate community strength. In the second part, we consider only positive interactions, but with the presence of inflexible agents holding a minority opinion. We also consider an indecision noise: a probability q that allows the spontaneous change of opinions to the neutral state. Our results show that the modular structure leads to a nonmonotonic global ordering as q increases. This inclination toward neutrality plays a dual role: a moderated propensity to neutrality helps the initial minority to become a majority, but this noise-driven opinion switching becomes less pronounced if the agents are too susceptible to become neutral.

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Section: Introductionmentioning

confidence: 99%

Three-state opinion dynamics in modular networks

2019

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“…Opinions can be modeled by a discrete variable, to account for a restricted number of options [4,[6][7][8][9][10][11][12][13][14][15][16][17][18][19]. For instance, the opinion o i of individual i can take the values -1,0,1, corresponding to the unfavorable, neutral and favorable attitudes.…”

Section: Introductionmentioning

confidence: 99%

Symmetry breaking by heating in a continuous opinion model

Anteneodo

Crokidakis

2017

Phys. Rev. E

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We study the critical behavior of a continuous opinion model, driven by kinetic exchanges in a fully connected population. Opinions range in the real interval [-1,1], representing the different shades of opinions against and for an issue under debate. Individuals' opinions evolve through pairwise interactions, with couplings that are typically positive, but a fraction p of negative ones is allowed. Moreover, a social temperature parameter T controls the tendency of the individual responses toward neutrality. Depending on p and T, different collective states emerge: symmetry broken (one side wins), symmetric (tie of opposite sides), and absorbing neutral (indecision wins). We find the critical points and exponents that characterize the phase transitions between them. The symmetry breaking transition belongs to the usual Ising mean-field universality class, but the absorbing-phase transitions, with β=0.5, are out of the paradigmatic directed percolation class. Moreover, ordered phases can emerge by increasing social temperature.

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“…In addition to the analytically tractable DeGroot and bounded confidence models we looked at in detail in this paper, there are simulation driven approachs to understanding models [88][89][90][91][92][93].…”

Section: Other Workmentioning

confidence: 99%

From classical to modern opinion dynamics

Noorazar,

Vixie,

Talebanpour

et al. 2019

Preprint

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In this age of Facebook, Instagram and twitter, there is rapidly growing interest in understanding network-enabled opinion dynamics in large groups of autonomous agents. The phenomena of opinion polarization, the spread of propaganda and fake news, and the manipulation of sentiment are of interest to large numbers of organizations and people, some of whom are resource rich. Whether it is the more nefarious players such as foreign governments that are attempting to sway elections or large corporations that are trying to bend sentiment -often quite surreptitiously, or it is more open and above board, like researchers that want to spread the news of some finding or some business interest that wants to make a large group of people aware of genuinely helpful innovations that they are marketing, what is at stake is often significant.In this paper we review many of the classical, and some of the new, social interaction models aimed at understanding opinion dynamics.While the first papers studying opinion dynamics appeared over 60 years ago, there is still a great deal of room for innovation and exploration. We believe that the political climate and the extraordinary (even unprecedented) events in the sphere of politics in the last few years will inspire new interest and new ideas.It is our aim to help those interested researchers understand what has already been explored in a significant portion of the field of opinion dynamics. We believe that in doing this, it will become clear that there is still much to be done.

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Opinion evolution in open community

Cited by 9 publications

References 22 publications

Three-state opinion dynamics in modular networks

Three-state opinion dynamics in modular networks

Symmetry breaking by heating in a continuous opinion model

From classical to modern opinion dynamics

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