https://doi.org/10.1140/epjp/s13360-025-06330-z
Regular Article
Phase transition in infection scale and the impact of user characteristics under the herd effect in information propagation
School of Computer and Communication, Lanzhou University of Technology, 730050, Lanzhou, Gansu, China
Received:
18
December
2024
Accepted:
14
April
2025
Published online:
12
May
2025
This study explores the phase transition phenomenon in information dissemination, focusing on how the herd effect influences the infection scale and the role of individual user characteristics in network propagation. First, we define two key components of the herd effect and analyze its impact on dissemination dynamics. Then, we investigate how individual user characteristics-user influence, cognitive level, and information demand affect the spread of information and construct a dynamic propagation model based on the SI propagation model. Through numerical simulations under various network conditions, we demonstrate that the herd effect can cause abrupt shifts in infection scale, significantly accelerating information propagation. Furthermore, we validate the model’s accuracy by comparing simulated data with the actual data using the Pearson correlation coefficient. The findings provide insights into the mechanisms driving rapid information spread and offer implications for controlling misinformation and optimizing information diffusion strategies.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
