Acta Scientific Orthopaedics (ISSN: 2581-8635)

Research Article Volume 6 Issue 3

Biostatistical Models of Breaking the "Scream Effect" and "Echo Chamber Effect”

Bin Zhao1* and Tongxi Yu2

1School of Science, Hubei University of Technology, Wuhan, Hubei, China
2University of California, Santa Barbara, CA, USA

*Corresponding Author: Bin Zhao, School of Science, Hubei University of Technology, Wuhan, Hubei, China.

Received: December 02, 2022; Published: February 07, 2023


This paper establishes a biostatistical model to describe the generation mechanism of neutral consensus and opinion polarization, explores the formation mechanism of the "screaming effect", "echo chamber effect" and "information cocoon room", and studies how to use reasonable strategies to avoid "Screaming effect" and "echo chamber effect” according to the biostatistical model built.

Keywords: Screaming Effect; Echo Chamber Effect; Information Cocoon


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  2. Wang Dandan and Yuxing “Echo Chamber Effect in Rumor Rebuttal Discussions About COVID-19 in China: Social Media Content and Network Analysis Study”. Journal of Medical Internet Research 23.3 (2021): e27009-e27009.
  3. “Quantifying Echo Chamber Effects in Information Spreading over Political Communication Networks.” EPJ Data Science 8.1 (2019): 1-13.
  4. Liu Wei and Wei Zhou. “Research on Solving Path of Negative Effect of “Information Cocoon Room” in Emergency.” Discrete Dynamics in Nature and Society 2022 (2022): 1-12.
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  6. Peng Hanqi and Chang Liu. "Breaking the Information Cocoon: When Do People Actively Seek Conflicting Information?" Proceedings of the Association for Information Science and Technology 1 (2021): 801-803.
  7. Guess Andrew., et al. "Avoiding the echo chamber about echo chambers”. Knight Foundation 2 (2018): 1-25.


Citation: Bin Zhao and Tongxi Yu. “Biostatistical Models of Breaking the "Scream Effect" and "Echo Chamber Effect””. Acta Scientific Orthopaedics 6.3 (2023): 41-52.


Copyright: © 2023 Bin Zhao and Tongxi Yu. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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