Cited by 669Complex Network Analysis TechniquesOpinion Dynamics and Social InfluenceComplex Systems and Time Series Analysis

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The “majority illusion” in social networks

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Lerman, Kristina, Yan, Xiaoran, Wu, Xin-Zeng·2016·PLOS ONE

DOI 10.1371/journal.pone.0147617PMC PMC4757419

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Abstract

Individual's decisions, from what product to buy to whether to engage in risky behavior, often depend on the choices, behaviors, or states of other people. People, however, rarely have global knowledge of the states of others, but must estimate them from the local observations of their social contacts. Network structure can significantly distort individual's local observations. Under some conditions, a state that is globally rare in a network may be dramatically over-represented in the local neighborhoods of many individuals. This effect, which we call the "majority illusion," leads individuals to systematically overestimate the prevalence of that state, which may accelerate the spread of social contagions. We develop a statistical model that quantifies this effect and validate it with measurements in synthetic and real-world networks. We show that the illusion is exacerbated in networks with a heterogeneous degree distribution and disassortative structure.

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Authors: Lerman, K., Yan, X., & Wu, X.-Z.
Affiliations: University of Southern California (US)
Corresponding author: Lerman, Kristina
ORCID: Lerman, Kristina
Yan, Xiaoran
Venue: PLOS ONE
Publisher: Public Library of Science (PLoS)
Published: 2016-02-17
Volume: 11
Issue: 2
Pages: e0147617
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0147617
PMC: PMC4757419
OpenAlex: W1552468722
Cited by: 669
References: 51
Citations by year: 2026: 11 · 2025: 13 · 2024: 15 · 2023: 26 · 2022: 22 · 2021: 135 · 2020: 123 · 2019: 119 · 2018: 94 · 2017: 78 · 2016: 30
FWCI: 60.61
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: PLoS ONE (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
arXiv (Cornell University) (submittedVersion)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Figshare (submittedVersion, cc-by)
arXiv (Cornell University)
Funders: National Science Foundation (1217605)
Defense Advanced Research Projects Agency (W911NF- 12-1-0034)
Advanced Research Projects Agency
Air Force Office of Scientific Research (FA9550-, FA9550-10-1-, FA9550-10-1-0569)
Topics: Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
Keywords: social networks, prevalence estimation, social contagion, network structure, degree heterogeneity, disassortative mixing, statistical models
MeSH terms: Humans, Illusions, Normal Distribution, Social Networking

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