Clarifying the relationship mechanism between perceived algorithmic recommendation accuracy and user satisfaction helps platforms optimize recommendation algorithms in a targeted manner and guide algorithms to be benevolent. Based on the Stimulus-Organism-Response (S-O-R) theory, this study constructs a theoretical model of how perceived algorithmic recommendation accuracy affects user satisfaction on short video platforms. By analyzing 398 valid questionnaires, the conclusions are drawn as follows: First, there is an inverted U-shaped relationship between perceived algorithmic recommendation accuracy and user satisfaction, which first increases and then decreases; second, algorithm fatigue plays a mediating role in the inverted U-shaped relationship between perceived algorithmic recommendation accuracy and user satisfaction; third, information-seeking motivation moderates the inverted U-shaped relationship between perceived algorithmic recommendation accuracy and user satisfaction.

Amid the global wave of digital government transformation, China and the United States have pursued markedly different development paths. This paper investigates the fundamental differences between the two countries’ approaches in terms of top-level design, technological applications, public participation, and the impact on privacy rights, as well as the underlying logic behind these differences. Through comparative case studies and policy text analysis, the research focuses on China’s “Health Code” and “One-Stop Online Services,” alongside the EU’s GDPR and California’s CCPA as core cases. The main findings are as follows: China’s path is state-led and efficiency-oriented, producing highly effective governance tools but facing the risk of a “Digital Leviathan”; the U.S./EU path prioritizes rights and checks and balances, building a “Digital Commons” at the potential cost of efficiency. Both approaches must confront their respective challenges and explore avenues for dialogue and mutual learning.

With the development of information network technology, crimes in cyberspace are also increasing. In view of the defamation behavior of using the cyber water army, it is found that it has the development trend of industrialization and concealment, and its serious harm to social order and individual rights and interests. By analyzing the characteristics of defamation in the cyber water army, which are different from traditional defamation in behavior mode and communication mechanism, this paper points out the difficulties faced by the current criminal law in subject identification, plot standard and prosecution procedure. Therefore, it is proposed that people should clearly crack down on the main sponsors and active participants, set quantifiable standards of seriousness of the circumstances, and promote the lowering of the threshold of public prosecution and the improvement of related crimes, so as to build a governance path that takes into account both the cracking effect and the modesty of criminal law.

This article discusses the copyright issues involved in China’s artificial intelligence-generated works, focusing on two core controversial points: “copyrightability” and “copyright attribution”. The article systematically reviews the different views of academic circles and judicial practice at home and abroad: in terms of copyrightability, supporters believe that the works generated by artificial intelligence meet the basic standards of originality and intellectual creation, while opponents emphasize that they lack human subjectivity and direct intellectual control. In terms of copyright attribution, the main views include the theory of artificial intelligence attribution, the theory of artificial intelligence user attribution and the theory of investor attribution. The author believes that the works generated by artificial intelligence should be copyrighted, and proposes to adopt the practice of “user ownership as the principle”. This method will include clarifying the legislation on the nature of the work, establishing a traceability mechanism, and limiting the protection period to a certain range to balance innovation incentives and public interests, so as to provide theoretical reference for China’s artificial intelligence copyright framework.