Reinforcement Mechanism of Information Cocoon Effect by AIGC Technology - Empirical Study of Information Retrieval Based on Affective Biases

Li Pengcheng; Zhang Jidong; Zhou Wenhui; Li Jie

doi:10.13266/j.issn.0252-3116.2026.10.007

2026 , Vol. 70 >Issue 10: 80 - 94

DOI: https://doi.org/10.13266/j.issn.0252-3116.2026.10.007

RESEARCH PAPERS

Reinforcement Mechanism of Information Cocoon Effect by AIGC Technology - Empirical Study of Information Retrieval Based on Affective Biases

Li Pengcheng ,
Zhang Jidong ,
Zhou Wenhui ,
Li Jie

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1 School of Economics and Management, Hubei University of Technology, Wuhan 430068;
2 Hubei Rural Social Management Innovation Research Center, Wuhan 430068;
3 School of E-Commerce, Wuhan Business College, Wuhan 430068;
4 Shandong University Library, Jinan 250100

Li Pengcheng, Lecture, PhD; Zhang Jidong, Professor, PhD, Doctoral Supervisor; Zhou Wenhui, Undergraduate Student; Li Jie, Librarian, PhD, Corresponding Author, E-mail: allison lijie@163.com.

Received date: 2025-04-08

Revised date: 2025-08-02

Online published: 2026-05-07

Supported by

This work is supported by the National Social Science Fund Youth Project “Empirical Research on Resource Recommendation Service Models in Smart Libraries from a Fuzzy Cognitive Perspective” (Grant No. 22CTQ009), and the Hubei University of Technology High-Level Talent Research Startup Fund Project “Research on the Automatic Generation of Relevant Chapters in Academic Texts Based on Hierarchical Semantic Function Perception” (Grant No. XJ2022009701).

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Abstract

[Purpose/Significance] Against the backdrop of AIGC technology reconstructing the information ecosystem, exploring the mechanism of generative artificial intelligence on the information cocoon effect holds significant theoretical value and social implications. [Method/Process] This study selects three representative information retrieval tools - Google, ChatGPT-4o, and Perplexity - as samples. Through designing and conducting controlled comparative experiments, we construct and introduce quantitative indicators including emotional bias, emotional polarization, and emotional diversity to comprehensively investigate the performance of AIGC technology in enhancing the homogenization of search results. Furthermore, combining case analysis, we deeply examine the mechanism of AIGC’s characteristic attributes in regulating information flow and influencing users’ cognitive diversity. [Results/Conclusion] Experimental findings reveal that compared with traditional search engines, AIGC-based search platforms demonstrate stronger tendencies to generate content aligned with users’ emotional preferences. Their returned results exhibit significantly higher emotional consistency, manifested through notably increased emotional bias and polarization indices, alongside significantly reduced emotional diversity. Simultaneously, AIGC achieves this reinforcement effect through its internal “cascade amplification” mechanism, which amplifies emotional bias at each stage of information processing. In addition, the study identified differences in strategy between different AIGC tools in implementing this mechanism, namely “high bias input” and “high intensity filtering”.

Key words： AIGC; information cocoon effect; information retrieval; emotional diversity

Cite this article

Li Pengcheng , Zhang Jidong , Zhou Wenhui , Li Jie . Reinforcement Mechanism of Information Cocoon Effect by AIGC Technology - Empirical Study of Information Retrieval Based on Affective Biases[J]. Library and Information Service, 2026 , 70(10) : 80 -94 . DOI: 10.13266/j.issn.0252-3116.2026.10.007

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