Paper Type
Complete
Paper Number
PACIS2025-1148
Description
Information cocoons are communication environments where individuals are exposed only to information aligned with their preferences, leading to a significant loss of information diversity. This study refines the concept and measurement of information cocoons, offering critical insights into their dynamic formation mechanisms. We define cocoons as a “loss of information diversity,” quantify this loss using entropy, and identify two key mechanisms: algorithmic filtering and self-selection. Specifically, we distinguish between the “selection cocoon,” driven by user-initiated choices, and the “recommendation cocoon,” shaped by platform algorithms. Analyzing 118,386 new social media users, we find that 55.7% fell into an information cocoon within a year, with self-selection playing a more significant role than algorithms. Particularly susceptible groups include less active users, young adults, women, high-income individuals, and residents of first-tier cities. This study provides a comprehensive framework for understanding information cocoons and offers valuable insights for promoting information diversity in digital environments.
Recommended Citation
Wang, Lin; Yang, Molin; Wang, Alex; Zhang, Jiayin; and Xu, Sean Xin, "Understanding the Dynamics of Information Cocoons on Social Media Platforms" (2025). PACIS 2025 Proceedings. 19.
https://aisel.aisnet.org/pacis2025/sm_digcollab/sm_digcollab/19
Understanding the Dynamics of Information Cocoons on Social Media Platforms
Information cocoons are communication environments where individuals are exposed only to information aligned with their preferences, leading to a significant loss of information diversity. This study refines the concept and measurement of information cocoons, offering critical insights into their dynamic formation mechanisms. We define cocoons as a “loss of information diversity,” quantify this loss using entropy, and identify two key mechanisms: algorithmic filtering and self-selection. Specifically, we distinguish between the “selection cocoon,” driven by user-initiated choices, and the “recommendation cocoon,” shaped by platform algorithms. Analyzing 118,386 new social media users, we find that 55.7% fell into an information cocoon within a year, with self-selection playing a more significant role than algorithms. Particularly susceptible groups include less active users, young adults, women, high-income individuals, and residents of first-tier cities. This study provides a comprehensive framework for understanding information cocoons and offers valuable insights for promoting information diversity in digital environments.
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