Analysis of Sudden Public Opinion Spread and Governance Paths Driven by Generative Artificial Intelligence

DOI

10.2991/978-2-38476-551-5_84How to use a DOI?

Keywords

Public opinion guidance; Emergency events; System dynamics; Public opinion risk

Abstract

Exploring the analysis of dissemination paths and governance approaches of sudden public opinion events driven by generative artificial intelligence (GAI) in the context of digital transformation and providing relevant references is of great significance. From the perspective of public opinion dissemination, this study analyzes the influencing factors of public opinion spread driven by GAI; improves the classical SIR model by incorporating the effects of these influencing factors on the dissemination process; and constructs a dynamic model of sudden public opinion events driven by GAI. Comparing the simulation results with the trend of actual case public opinion volume shows that both trends are generally consistent, validating the model’s accuracy.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xiao Wang
AU  - Gaoyue Zhao
PY  - 2026
DA  - 2026/03/26
TI  - Analysis of Sudden Public Opinion Spread and Governance Paths Driven by Generative Artificial Intelligence
BT  - Proceeding of 2025 8th International Conference on Humanities Education and Social Sciences (ICHESS 2025)
PB  - Atlantis Press
SP  - 777
EP  - 783
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-551-5_84
DO  - 10.2991/978-2-38476-551-5_84
ID  - Wang2026
ER  -