Public Discourse and Social Network Echo Chambers Driven by Socio-Cognitive Biases

Wang, Xin; Sirianni, Antonio D.; Tang, Shaoting; Zheng, Zhiming; Fu, Feng

doi:10.1103/physrevx.10.041042

Cited by 63 publications

(68 citation statements)

References 51 publications

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“…It naturally provides us with an insight on how to persuade individuals with moderate opinions when the system has reached a steady state. To guide "confident moderates, " it is required to continually inform them on opinions close to their beliefs because confident individuals only value opinions within their identity scope, which is consistent with previous studies [44]. On the contrary, to guide "impressionable moderates, " deploying zealots with extreme views might be an efficient strategy because impressionable individuals are more likely to be forced to readjust their opinions according to the surroundings.…”

Section: Thus Some Impressionable Individuals Would Have Opinions Famentioning

confidence: 53%

“…According to the well-known confirmation bias, agents just think that opinions that are close enough to their beliefs are reasonable and that corresponding neighbors are supporters of their cognition. Complying with previous studies [44], we define δ as the identity scope to describe the phenomena. Specifically, neighbor j is recognized as a supporter by agent…”

Section: Modelmentioning

confidence: 99%

“…The phenomena are ubiquitous in many real-world scenarios of opinion evolution. A well-known case is The USA Presidential election where people finally form three groups according to their political opinions: Democratic supporter group, Republican supporter group, and the moderate group [44]. In this case, the moderate group plays a very significant role as their choices directly determine the winner in competing processes.…”

Section: Thus Some Impressionable Individuals Would Have Opinions Famentioning

confidence: 99%

“…Sîrbu et al proposed a multi-dimensional dynamical model incorporating the possibility of the disagreement among discordant pairs and the effect of mass media, which illustrated the important roles of the initial condition, dimensions, as well as the external information system [42,43]. Wang et al introduced an agent-based model integrating external political campaigns and opinion dynamics, which reproduced the 2016 USA presidential election well and yielded intriguing moderate clusters in addition to two polarized clusters [44].…”

Section: Introductionmentioning

confidence: 99%

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Modeling Confirmation Bias and Peer Pressure in Opinion Dynamics

et al. 2021

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Confirmation bias and peer pressure are regarded as the main psychology origins of personal opinion adjustment. Each show substantial impacts on the formation of collective decisions. Nevertheless, few attempts have been made to study how the interplay between these two mechanisms affects public opinion evolution on large-scale social networks. In this paper, we propose an agent-based model of opinion dynamics which incorporates the conjugate effect of confirmation bias (characterized by the population identity scope and initiative adaptation speed) and peer pressure (described by a susceptibility threshold and passive adaptation speed). First, a counterintuitive non-monotonous phenomenon arises in the homogeneous population: the number of opinion clusters first increases and then decreases to one as the population identity scope becomes larger. We then consider heterogeneous populations where “impressionable” individuals with large susceptibility to peer pressure and “confident” individuals with small susceptibility coexist. We find that even a small fraction of impressionable individuals could help eliminate public polarization when population identity scope is relatively large. In particular, the impact of impressionable agents would be greater if these agents are hubs. More intriguingly, while impressionable individuals have randomly distributed initial opinions, most of them would finally evolve to moderates. We highlight the emergence of these “impressionable moderates” who are easily influenced, yet are important in public opinion competition, which may inspire efficient strategies in winning competitive campaigns.

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Section: Thus Some Impressionable Individuals Would Have Opinions Famentioning

confidence: 53%

Section: Modelmentioning

confidence: 99%

Section: Thus Some Impressionable Individuals Would Have Opinions Famentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling Confirmation Bias and Peer Pressure in Opinion Dynamics

et al. 2021

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“…This may be because humans evolved, when hunter gathers, to place emphasis on knowledge considered most important for survival [107] and individuals typically seek to survive through inclusion within groups [108,109]. Hence, individuals may seek to survive by learning from filtered information that supports the preconceptions of groups, which they believe can support their individual survival [110,111] rather than seek information that supports the efficient reduction of prediction errors in external states.…”

Section: Prediction Errorsmentioning

confidence: 99%

Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Fox

2021

Entropy

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Active inference is a physics of life process theory of perception, action and learning that is applicable to natural and artificial agents. In this paper, active inference theory is related to different types of practice in social organization. Here, the term social organization is used to clarify that this paper does not encompass organization in biological systems. Rather, the paper addresses active inference in social organization that utilizes industrial engineering, quality management, and artificial intelligence alongside human intelligence. Social organization referred to in this paper can be in private companies, public institutions, other for-profit or not-for-profit organizations, and any combination of them. The relevance of active inference theory is explained in terms of variational free energy, prediction errors, generative models, and Markov blankets. Active inference theory is most relevant to the social organization of work that is highly repetitive. By contrast, there are more challenges involved in applying active inference theory for social organization of less repetitive endeavors such as one-of-a-kind projects. These challenges need to be addressed in order for active inference to provide a unifying framework for different types of social organization employing human and artificial intelligence.

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Final Thoughts: Explaining Ideological Possession

Cotterill

2023

Personality Psychology, Ideology, and Voting Behavior: Beyond the Ballot

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Public Discourse and Social Network Echo Chambers Driven by Socio-Cognitive Biases

Cited by 63 publications

References 51 publications

Modeling Confirmation Bias and Peer Pressure in Opinion Dynamics

Modeling Confirmation Bias and Peer Pressure in Opinion Dynamics

Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Final Thoughts: Explaining Ideological Possession

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