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◆ Information2025-10-01· Public opinion

Speaking like Humans, Spreading like Machines: A Study on Opinion Manipulation by Artificial-Intelligence-Generated Content Driving the Internet Water Army on Social Media

Jinghong Zhou, Dandan Zhang, Jiawei Zhu, Fan Wang, Chongwu Bi

原始摘要(英文原文)· Original abstract
This study focuses on the evolution of the Internet Water Army on social media, identifying a novel form known as artificial-intelligence-generated-content-enhanced social bots (AESBs), and compares their structural influence with traditional social bots in the context of public opinion guidance. Based on 3 years of real-world data from Weibo, this study develops a comprehensive framework integrating bot account detection, AESB content identification, and quantitative assessments of opinion guidance. A large-scale opinion propagation network is constructed to examine the structural roles of traditional social bots and AESB across three analytical levels: the node, community, and overall network. The results reveal substantial differences between AESB and traditional social bots. Social bots play a limited guiding role but help maintain network connectivity. In contrast, AESBs produce highly consistent and human-like content that demonstrates a significant capacity to reinforce topic focus, amplify emotional homogeneity, and deepen diffusion pathways, indicating a shift toward strategic content manipulation. These results suggest that AESBs are not merely passive generators but active agents of structural opinion control, capable of combining human mimicry with machine-level efficiency. This study advances theoretical understanding of IWA manipulation mechanisms, provides a replicable methodological approach, and offers practical implications for platform governance.
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Speaking like Humans, Spreading like Machines: A Study on Opinion Manipulation by Artificial-Intelligence-Generated Content Driving the Internet Water Army on Social Media — 科研速览 Science Skim