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25 August 2025, Volume 45 Issue 04
    

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  • The Classification, Development Status, and Trend Analysis of Global Artificial Intelligence Evaluation Index Systems
    Luo Liqun Li Guangjian
    Library & Information. 2025, 45(04): 1-14. DOI:10.11968/tsyqb.1003-6938.2025041
    Abstract ( ) Download PDF ( ) Knowledge map Save
    Artificial intelligence evaluation index systems not only serve as a weather vane for the innovative development of global AI but also implicitly reflect the national will and strategic interests of their originating countries. This paper begins by reviewing 22 representative AI evaluation indices from around the world. Based on the evaluation subjects and objectives, it constructs a classification framework for AI evaluation index systems, comprising five categories: comprehensive strength, development foundation, R&D capabilities, ethics and governance, and market application. Secondly, the paper provides an analysis of the differences among these various evaluation index systems in terms of their goal-setting, areas of emphasis in their indicators, and methodologies, revealing the underlying national strategies, policy orientations, and values. Finally, it systematically analyzes four major trends in current global AI evaluation index systems from the perspectives of evaluation paradigms, the right to discourse in evaluation, evaluation objectives, and the timeliness of evaluation.
  • Structural Deconstruction and Paradigm Analysis of Global AI Evaluation Indicator Systems
    Li Xiang Li Guangjian Luo Liqun
    Library & Information. 2025, 45(04): 15-24. DOI:10.11968/tsyqb.1003-6938.2025042
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    The global artificial intelligence (AI) evaluation system faces challenges of "measurement black boxes" and "strategic misjudgments." To systematically deconstruct its internal structure, this study integrates 22 mainstream AI evaluation indexes (637 original indicators), constructs a standardized library of 307 comparable indicators, and uses a dual-dimensional analysis (attention distribution and complex network modeling) to reveal its internal operational logic. The study, for the first time, identifies and names the dominant "national capacity-based, scale-oriented growth" evaluation paradigm in the field. This paradigm takes national capacity as its evaluation core, is driven by a "policy-technology" dual engine, exhibits a significant scale-oriented bias in its measurement standards, and consequently has structural blind spots in dimensions such as innovation quality and conversion efficiency. By providing a structural blueprint of this paradigm, this study offers a critical empirical pathway for avoiding strategic misjudgments and designing more balanced next-generation evaluation frameworks.
  • Research on Global Artificial Intelligence Evaluation Indicator Systems Based on Ranking Performance
    Wang Chuhan Li Guangjian Chen Mo
    Library & Information. 2025, 45(04): 23-35. DOI:10.11968/tsyqb.1003-6938.2025043
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    Against the backdrop of intensifying global artificial intelligence (AI) competition, frequent fluctuations in national rankings across evaluation indices not only reflect shifts in national capabilities but also reveal how index design logic influences and shapes assessment outcomes. To interrogate this phenomenon, this paper first selected nine mainstream AI evaluation indices as research samples based on five principles: representativeness, professionalism, relevance, transparency, and timeliness. Using the TF-IDF algorithm for taxonomic categorization of original indicators, five thematic dimensions were identified: Data Infrastructure, Talent Pool, R&D Capacity, Investment & Deployment, and Strategy & Governance. Employing this framework, we conducted cross-sectional comparisons of scores across these dimensions for 15 leading nations and longitudinal tracking of their rank variations across indices and time periods. Key findings indicate that: Ranking volatility stems primarily from adjustments in indicator weighting schemas and scoring granularity, with indices embedding distinct technological priorities and value orientations; The Strategy & Governance dimension exhibits high reactivity to policy signals, while other dimensions demonstrate greater temporal stability. This research proposes a standardized five-dimensional evaluation architecture incorporating dynamic weight calibration and an annual rolling revision mechanism. This approach achieves dynamic equilibrium between international comparability and contextual adaptation, providing methodological scaffolding for constructing versatile yet responsive AI assessment frameworks.
  • Construction of an International Influence-Oriented Evaluation System for AI Development with Chinese Characteristics
    Wu Xuan Li Guangjian Pan Jiali
    Library & Information. 2025, 45(04): 36-48. DOI:10.11968/tsyqb.1003-6938.2025044
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    International influence in artificial intelligence serves as a pivotal benchmark for assessing a nation’s technological competitiveness. This study addresses the limitation that existing evaluation systems, constructed on traditional factors such as talent, data, and capital, struggle to effectively assess the critical dimensions of China’s international influence in artificial intelligence. It develops a China-specific evaluation framework incorporating multidimensional indicators. The methodology proceeds in three stages: a systematic review of global research trends on AI international influence; development of a hierarchical influence model integrating academic, technological, industrial, and organizational dimensions and design of a multi-tiered evaluation system featuring 4 primary indicators, 15 secondary indicators, and 44 tertiary indicators, with weights determined through the Analytic Hierarchy Process (AHP). This framework provides quantitative tools for China to accurately position itself within the global AI landscape, enhances its discourse power and influence, and offers theoretical support for optimizing strategic layout and development paths in China’s AI domain.
  • Research Landscape and Paradigm Reshaping in the Field of Scientific and Technological Information in the AI4S Era
    Cao Shujin Cao Ruye
    Library & Information. 2025, 45(04): 49-60. DOI:10.11968/tsyqb.1003-6938.2025045
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    With the rapid development of artificial intelligence, a new research paradigm, "Artificial Intelligence for Science (AI4S)," has emerged and is reshaping the fundamental logic of scientific research. Exploring the impact of AI4S on research in the field of scientific and technical information and its response mechanisms will help provide theoretical support and guidance for the future development of scientific and technical information science. This article reviews the landscape of scientific and technical information research in the AI4S era, conducts topic identification and evolution analysis based on BerTopic and LLM, and summarizes the responsiveness and limitations of scientific and technical information research to AI4S. Furthermore, it discusses the paradigm shift and problem reconstruction in the field of scientific and technical information under the influence of AI4S. A new paradigm for scientific and technical information research in the AI4S era is proposed from the perspectives of theoretical logic, research objects, research perspectives, and functional positioning. Moreover, the shift of research problems is analyzed with respect to traditional and new research tasks in the field of scientific and technological information. The study finds that current research in the field of scientific and technical information focuses more on "leveraging readily available data intelligence to greatly facilitate intelligent information." Future research should explore information-based intelligence in -depth, fully leveraging the leading role of scientific and technical information.
  • Research on the Construction of Large Language Model - Driven Fact-Checking Multi-Agent System
    Zhu Mengdie Guan Zhenkai Wang Yi Yang Haiping
    Library & Information. 2025, 45(04): 61-72. DOI:10.11968/tsyqb.1003-6938.2025046
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    Against the backdrop of globalization marked by political and economic turbulence, intensifying climate change, and accelerated technological innovation, the information dissemination ecosystem has grown increasingly complex. The proliferation of disinformation has emerged as an urgent issue threatening social stability, public health, and political security. First of all, This paper focuses on the innovative application of large language model-driven agents in the field of fact-checking to address the challenges of disinformation governance in complex scenarios. In the next place, it systematically examines the current challenges faced in fact-checking and demonstrates the potential and advantages of empowering fact-checking work through large language model-driven multi-agent. This research designed the theoretical framework of the large language model-driven fact-checking multi-agent system, outlined a practical path for collaborative work among large language model-driven fact-checking multi-agent through empirical research, and verified the superior performance of the system through comparative experiments.
  • The Governance of Public Digital Culture: A Review of the 14th Five-Year Plan and Prospects for the 15th Five-Year Plan
    Shi Qinggong Feng Wei Wang Zijian Zhou Lihong
    Library & Information. 2025, 45(04): 73-82. DOI:10.11968/tsyqb.1003-6938.2025047
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    Public digital cultural governance (GPDC) is a key driver for high-quality public digital cultural services and a crucial extension of China's modernization of national governance and Digital China strategy. Through literature review and online investigation, this article synthesizes the research hotspots, practice progress, and problems in GPDC during the 14th Five-Year Plan period. Despite notable achievements, theoretical gaps still remain, including the incomplete governance framework, the under-researched public participation mechanism, and the unfinished shift from "management" to "governance". Practically, problems are still existent in certain fields, such as the construction of data governance mechanisms and the evaluation of policy implementation. During the 15th Five-Year Plan period, it is suggested to enhance effectiveness of GPDC through institutional improvements and innovative mechanisms. This involves streamlining high-level coordination mechanisms based on a robust national institutional framework, exploring innovative systems for digital resources centered around Chinese culture, strengthening mechanisms for public participation in the integration of digital culture and smart tourism, ensuring that high-quality resources embedded with artificial intelligence reach grassroots levels, and innovating digital public cultural service mechanisms in rural areas.
  • Research on the Adoption of AIGC Health Information Driven by Dual Factors of AI Literacy and Health Information Literacy
    Zhang Jinao Lu Xinyuan Wang Durong Cai Xingxing
    Library & Information. 2025, 45(04): 83-95. DOI:10.11968/tsyqb.1003-6938.2025048
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    Exploring the relationships, mechanisms, and configurational paths between artificial intelligence literacy, health information literacy, and AIGC health information adoption is fundamental for optimizing human-AI interaction processes and standardizing information behaviors. This paper employs multi-stage experiments, structural equation modeling, and configurational analysis to examine the influence of artificial intelligence literacy, health information literacy, and AIGC health information adoption. Research findings indicate that artificial intelligence literacy and health information literacy have a positive impact on the adoption of AIGC health information, and perceived system quality and perceived information quality are important influencing paths, which further expand the information adoption model. At the same time, perceived knowledge consensus can also drive trust and the adoption of AIGC health information by acting on perceived system quality and perceived information quality, which reflects the multi-source information verification relationship of individuals towards AI-generated content. In addition, configuration analysis reveals that, apart from the trust-system dominant configuration adoption mode led by trust and perceived system quality, there are two other adoption modes, namely the ethics-oriented configuration and the evaluation-oriented configuration. This also provides a directional basis for regulating the adoption behavior of AIGC health information.
  • The Influence of Health Information Fidelity on Patient Trust in Preoperative Communication Situation
    Sun Xinxin Kang Yuanyuan Zhang Liman Zhao Yuxiang
    Library & Information. 2025, 45(04): 96-108. DOI:10.11968/tsyqb.1003-6938.2025049
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    As the carrier of preoperative communication and health information transmission, auxiliary tools directly affect the quality of patients' perception of medical treatment. The development in the age of digital intelligence has further improved the digitalization level of communication tools, but the influence of the fidelity of health information on communication quality and its potential mechanism still need to be studied. Therefore, this study discusses the influence of health information fidelity on doctor-patient trust, and explores the synergy between picture types and information fidelity. Focusing on the operation of nevus excision in dermatology, we recruited subjects (N=318) and conducted a 2 (picture type: static/dynamic) ×3 (fidelity: low/medium/high) inter-group experiment, and discussed the effectiveness of preoperative communication tools from the dimensions of health information awareness, doctor-patient communication experience and trust. The results show that there is an interactive effect between the fidelity of health information and picture types, and the medium fidelity of health information and dynamic pictures are the most beneficial combination for patients to understand and communicate with their doctors. In addition, information awareness and communication experience play a chain intermediary role in the process that the fidelity affects patients' trust. 
  • The Multidimensional Architecture of Online Consultation Patients under the Attribute of "Super-Information": A Study Based on Grounded Theory
    Ma Ping Chen Shubing
    Library & Information. 2025, 45(04): 109-120. DOI:DOI：10.11968/tsyqb.1003-6938.2025050
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    Online Medical consultations are characterized by a "super-information" attribute that emerges from the integration of medical services, information services and data support. To examine how patients form trust under this attribute, the study employs a constructivist grounded-theory approach and conducts semi-structured interviews with 40 online-consultation patients. Findings reveal that patient trust is generated within a multidimensional information context comprising three interrelated layers: micro-level individual perceptual information, meso -level platform data information, and macro-level institutional information environment. Interactions among these layers of trust ultimately shape patients’ information-adoption behaviors. By analyzing patient trust through a multidimensional framework, this study addresses the previous neglect of the platform’s information ecology. The proposed framework provides theoretical insights into the logic of patient trust in online consultations and offers guidance for the development of health-information service systems.
  • Dynamic Evolution Analysis of Interdisciplinary Researchers’ Collaborative Willingness from the Perspective of Resilience in the Science and Technology Innovationn 
    Hu Wenjing Mei Hong Liu Ruijia
    Library & Information. 2025, 45(04): 121-132. DOI:10.11968/tsyqb.1003-6938.2025051
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    Interdisciplinary cooperation willingness serves as the core micro-foundation supporting the resilience of technological innovation, yet its practical dilemma of "high initial willingness but low sustainability" restricts the improvement of China's innovation system efficiency. To explore this dynamic fluctuation law, based on evolutionary game theory and interdisciplinary collaboration theory, this paper focuses on three core mechanisms: academic power balance, benefit distribution, and expected returns, constructs a tripartite evolutionary game model between research platforms and researchers from different disciplines, and analyzes the impact of key variables on cooperation willingness through simulation. The study finds that: Academic power balance is the core of stable cooperation; moderate disciplinary differences can stimulate cooperation willingness, while power imbalance prolongs the stabilization cycle, with task centrality serving as a regulatory tool. The fairness of benefit distribution determines cooperation resilience; unfair distribution is prone to cause systemic risks, which can be adjusted by subdividing implicit and explicit benefits in line with the cooperation stages. Appropriate punishment mechanisms are more conducive to guiding cooperation than incentives. Corresponding policy suggestions such as hierarchical response, power checks and balances, fair distribution, and scientific rewards and punishments are put forward, providing a theoretical basis for building the stability of interdisciplinary cooperation and a decision-making reference for improving the more resilient technological innovation system.
  • Research on Users' Intention to Read Privacy Policies of Government Open Data Websites——A Hybrid Study Based on SEM-fsQCA
    Chen Mei Munire Tulafu Huang Rongxia
    Library & Information. 2025, 45(04): 133-144. DOI:10.11968/tsyqb.1003-6938.2025052
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    Explores the factors influencing users' willingness to read privacy policies on government open data platforms, analyzes the multi-factor configuration pathways, and uncovers the underlying mechanisms of users' willingness to engage with privacy policies. The findings aim to provide theoretical support and practical guidance for enhancing users' privacy awareness and optimizing privacy policy design. Based on the extended privacy calculus theory and the UTAUT2 model, this study first collected data through surveys and used structural equation modeling (SEM) to analyze the direct effects of factors such as privacy concerns, privacy protection intentions, performance expectancy, and social influence on users' willingness to read privacy policies. Then, fuzzy set qualitative comparative analysis (fsQCA) was applied to identify multi-factor configuration pathways and reveal the multiple driving logics behind users' privacy policy reading intentions. The study found that the key factors influencing users' willingness to read privacy policies include privacy concerns, privacy protection intentions, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and habits. Trust and social influence were found to have insignificant effects. Three main configuration pathways were ultimately identified: privacy-sensitivity, social trust, and convenience-dependence. Based on these findings, recommendations were made to simplify the language of privacy policies, improve the user interface design of privacy policies, and enhance users' trust in privacy protection.
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