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Cited by 18Misinformation and Its ImpactsComplex Network Analysis TechniquesSocial Media and Politics

Dense and influential core promotion of daily viral information spread in political echo chambers

Open access
Asatani, Kimitaka, Yamano, Hiroko, Sakaki, Takeshi, Sakata, Ichiro·2021·Scientific Reports
DOI 10.1038/s41598-021-86750-wPMC PMC8021571
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Abstract

Despite the intensive study of the viral spread of fake news in political echo chambers (ECs) on social networking services (SNSs), little is known regarding the underlying structure of the daily information spread in these ECs. Moreover, the effect of SNSs on opinion polarisation is still unclear in terms of pluralistic information access or selective exposure to opinions in an SNS. In this study, we confirmed the steady, highly independent nature of left- and right-leaning ECs, both of which are composed of approximately 250,000 users, from a year-long reply/retweet network of 42 million Japanese Twitter users. We found that both communities have similarly efficient information spreading networks with densely connected and core-periphery structures. Core nodes resonate in the early stages of information cascades, and unilaterally transmit information to peripheral nodes. Each EC has resonant core users who amplify and steadily spread information to a quarter of a million users. In addition, we confirmed the existence of extremely aggressive users of ECs who co-reply/retweet each other. The connection between these users and top influencers suggests that the extreme opinions of the former group affect the entire community through the top influencers.

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  • Specific hub nodes play a pivotal role in spreading misinformation within networks and shaping echo chambers.

    “Specific hub nodes play a pivotal role in spreading misinformation within networks and shaping echo chambers [99].”

    From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [99]

    The Results (pp. unavailable) show that top influencers spread large amounts of information within political echo chambers and suggest that their connected networks may contribute to opinion homogeneity. The paper does not establish that the information these hubs spread is misinformation; its Introduction distinguishes its study of daily information spread from earlier studies focused on fake news or rumours. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • The Louvain algorithm, Leiden algorithm, random walk modelling, greedy algorithms, latent space models, flow stability or hierarchical clustering algorithms are used in most cases of the included studies to detect communities in the bipartite graph.

    “The Louvain algorithm, 10 Leiden algorithm 11 (e.g., [99]), random walk modelling (e.g., [108, 127]), greedy algorithms (e.g., [94]), latent space models 12 (e.g., [8,100]), flow stability (e.g., [146]) or hierarchical clustering algorithms (e.g., [90]) are used in most cases of the included studies to detect communities in the bipartite graph.13”

    From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [99]

    The Methods section (‘Detection of political ECs and other communities’; page unavailable) says the study used Leiden clustering to detect communities, supporting its citation as an example of that algorithm. But it describes a network of users linked by replies and retweets, not a bipartite graph. This source also does not establish the citing review’s ‘most cases’ characterization. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • Node-level homophily focuses on individual tendencies to connect with similar users.

    “Node-Level Homophily: Focuses on individual tendencies to connect with similar users (e.g., [73,99]).”

    From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [99]

    The Introduction links homophily to individual cognitive and psychological behaviour, and the Results section on the connected core assumes that users with the same opinion connect with each other. The paper does not identify or define a distinct concept called “node-level homophily,” so it supports the underlying idea but not that specific framing. The indexed copy provides no page numbers for these passages. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • Network-level homophily measures the overall homophily of a network to understand the systemic tendencies for like-minded clustering.

    “Network-Level Homophily: Measures the overall homophily of a network to understand the systemic tendencies for like-minded clustering [99,117].”

    From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [99]

    The Introduction discusses how homophily can emerge, and the Methods section describes clustering users by reply and retweet relationships. Neither section defines or uses a network-level homophily measure to assess overall like-minded clustering (searched: “network-level homophily,” “homophily measure,” and “homophily”). No page numbers are available in our copy. (LLM, conf=0.73)

    Experimental — accuracy not yet measured

  • User leaning was also estimated by activity in specific groups, by semantics in the posts, calculation of political slant of visited websites by the user, and shared news URLs with news outlets leaning score.

    “User leaning was also estimated by activity in specific groups (e.g., [59,127,143]), by semantics in the posts (e.g., [94,99,113]), calculation of political slant of visited websites by the user [124], shared news URLs with news outlets leaning score (e.g., [8,96,129]).”

    From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [99]

    The citation to this paper appears in the clause about estimating user leaning from shared news URLs and news outlets’ leaning scores. The Results section (“Independent and steady political echo chambers”; page unavailable) identifies left- and right-leaning communities using reply/retweet relationships and notes liberal and conservative news media among influential accounts. It does not describe scoring shared news URLs or using outlet-leaning scores to estimate users’ leanings; searches for those methods found no supporting passage. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Asatani, K., Yamano, H., Sakaki, T., & Sakata, I.
Affiliations
  • The University of Tokyo (JP)
  • Institute for Future Initiatives, The University of Tokyo (JP)
Corresponding author
Asatani, Kimitaka
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2021-04-05
Volume
11
Issue
1
Pages
7491-7491
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-021-86750-w
PMC
PMC8021571
OpenAlex
W3141593921
Cited by
18
References
7
Citations by year
2026: 1 · 2025: 5 · 2024: 3 · 2023: 5 · 2022: 4
FWCI
3.81
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • New Energy and Industrial Technology Development Organization (P15009)
  • Kaken (19H02384)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
  • Social Sciences › Communication › Social Media and Politics
Keywords
fake news, core-periphery structure, influential users, opinion polarization, selective exposure, Twitter, information cascades, social media

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