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Identification, Evolution, and Prospects of Global Information Literacy Education Research Themes in 1974—2024 Huang Ruhua　Wu Yingqiang　Shi Leyi Journal of Information Resources Management    2025, 15 (4): 4-22.   DOI: 10.13365/j.jirm.2025.04.004 Abstract （1172）      PDF（pc） （5120KB）（206）       Knowledge map    Save The year 2024 marks the 50th anniversary of the introduction of the term information literacy on a global scale. This study applies the BERTopic topic modeling method to identify 44 major research topics in global information literacy education over the past five decades. These topics are categorized into five thematic clusters: (1) pedagogical practices in information literacy education, (2) information literacy education driven by digital and intelligent technologies, (3) information literacy education targeting specific populations, (4) disciplinary applications of information literacy education, and (5) social and ethical issues in information literacy education. Five key topics are highlighted: librarian-faculty collaboration in higher education, nurses’ information literacy, health information literacy, teachers’ ICT competence and skill development, and information literacy in the context of artificial intelligence. By tracking topic-specific keywords, this study outlines five stages in the evolution of research: the conceptual dissemination stage, the technological impact stage, the connotation expansion stage, the convergence of multiple literacies stage, and the stage influenced by major societal events. Over the past 50 years, three prominent characteristics have shaped the development of global information literacy education research: (1) consistent focus on higher education and academic libraries across all stages; (2) a distinct phase-based impact of technology on information literacy education; and (3) the influence of changing educational environments on the content and form of information literacy instruction. Finally, six future directions are proposed for global research and practice in information literacy education: strengthening theoretical study of information literacy education, emphasizing the development of standards and assessment systems, diversifying the contexts for information use, enhancing the roles of both the academic library community and the information industry, fostering nationwide collaboration, and boosting China’s international influence in the field. Related Articles | Metrics | Comments（0）

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Deepfake Information in AIGC: Generation Mechanisms and Governance Strategies: An Analytical Framework Based on Actor-Network Theory Ran Lian　Zhang Wei Journal of Information Resources Management    2025, 15 (2): 137-150.   DOI: 10.13365/j.jirm.2025.02.137 Abstract （1002）      PDF（pc） （2326KB）（1494）       Knowledge map    Save Exploring the complex logical mechanisms behind AIGC-driven deepfake information generation has significant practical value for constructing a cognitive framework for understanding deepfake information and formulating targeted governance strategies in cyberspace. Drawing on the actor-network theory, this study constructs a theoretical framework for analyzing AIGC deepfake information generation, focusing on four aspects: problem presentation, allocation of benefits, mobilization, and exclusion of dissent. It further interprets the dynamic process of deepfake information generation in terms of network formation, alliance-building, and stabilization. The findings indicate that the continuous output of AIGC-generated deepfake information is likely to intensify adverse social effects, such as technological domination, truth decay, and moral dissolution. The production and dissemination of deepfake information involve AIGC technologies translating heterogeneous actors through interest-driven strategies, driving the deepfake interest network from formation to stabilization while engaging in a competitive dynamic with opposing organizations. Based on these findings, this study proposes targeted governance strategies for AIGC deepfake information across four dimensions: moral governance, rule of law, technological governance, and crowd-based governance. Related Articles | Metrics | Comments（0）

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Experts in Information Resource Management Discipline Discussing "The 2024-2035 Master Plan on Building China into a Leading Country in Education"(Part 1): Talent Cultivation and Digital Literacy Education Sun Jiangjun Wu Dan Sun Xin Zhang Jiuzhen Huang Ruhua Li Yanke Journal of Information Resources Management    2025, 15 (2): 4-12.   DOI: 10.13365/j.jirm.2025.02.004 Abstract （854）      PDF（pc） （790KB）（5026）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Exploring a Multi-factor Model of Privacy Disclosure in User-Generative AI Interaction Sun Guoye　Wu Dan　Liu Jing　Deng Yuyang Journal of Information Resources Management    2025, 15 (2): 108-122.   DOI: 10.13365/j.jirm.2025.02.108 Abstract （704）      PDF（pc） （5021KB）（1100）       Knowledge map    Save The widespread application of generative artificial intelligence (Generative AI) has brought unique privacy challenges to human-computer interaction. This study focuses on privacy disclosure in the interaction between users and Generative AI, combining large language models with manual coding to identify common types of privacy disclosed in the interaction between users and Generative AI. Based on contextual integrity theory, this study employs user annotation and semi-structured interviews to explore the mechanisms influencing user privacy disclosure. The findings reveal that user privacy disclosure is jointly affected by the user's privacy attitude, technology trust, and privacy risk perception, and the system's data management transparency indirectly affects privacy disclosure by affecting technology trust. Based on the research results, this study constructs a multi-factor influence model of privacy disclosure in the interaction between users and Generative AI, providing a theoretical reference for the development of more privacy-friendly Generative AI. Related Articles | Metrics | Comments（0）

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Multidisciplinary Intersection and Multi-Scenario Embedding:Review of Domestic and International Research on Data Ethics Zhang Chuhui　Li Zhuozhuo　Pei Lei Journal of Information Resources Management    2025, 15 (2): 91-107.   DOI: 10.13365/j.jirm.2025.02.091 Abstract （642）      PDF（pc） （1589KB）（1798）       Knowledge map    Save In the age of digital intelligence, conflicts in data ethics arising from the exploitation and utilization of data have become increasingly pronounced, challenging societal governance structures and value systems. Research on data ethics has thus emerged as a shared concern across multiple disciplines. This paper adopts a systematic review method to analyze relevant literature, synthesizing data ethics theories and summarizing the core issues in data ethics research. Current studies demonstrate a clear trend toward interdisciplinary integration, with data ethics governance practices embedded across diverse digital contexts. Both theoretical and practical dimensions exhibit characteristics of multidisciplinarity and multi-contextuality. However, there remains significant scope to enhance the systematic, comprehensive, collaborative, and normative aspects of data ethics research. Future studies could explore three key directions: effectively linking empirical and normative research on data ethics, advancing interdisciplinary integration in data ethics studies, and transitioning from context-specific applications to holistic research addressing broader data governance ecosystems. Related Articles | Metrics | Comments（0）

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The Development Pattern, Dilemmas, and Countermeasures of Government-Led Data Trading Platforms：An Analysis Based on Classical Grounded Theory Hua Meifang　Zhang Yong Journal of Information Resources Management    2025, 15 (2): 73-90.   DOI: 10.13365/j.jirm.2025.02.073 Abstract （557）      PDF（pc） （3045KB）（2776）       Knowledge map    Save Government-led data trading platforms are spearheading the robust development of China's data factor market. This study focuses on five bench mark platforms, employing the classical grounded theory framework to analyze their development patterns and challenges. The findings reveal that their developmental models can be summarized into five key elements: policy guidance, developmental strategies, standardization construction, platform services, and the cultivation of a digital business ecosystem. However, these platforms face several challenges, including a lack of core competitiveness, insufficient interconnectivity, pronounced data silos, and limited transaction scales. To address these challenges, platforms need to expand their market influence through differentiated positioning, joint construction of a standardized interconnected ecosystem, collaborative development of digital business alliances, and active expansion of bilateral user groups. Meanwhile, the National Data Administration should undertake overall planning for platform deplayment, strengthen integrated security supervision, and establish a robust safety framework to ensure the healthy development of the market. Related Articles | Metrics | Comments（0）

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Evaluation of Prompt Fine-Tuning Data Efficacy in Large Language Models： A Focus on Data Quality Liu Xiaohui　Ran Congjing　Liu Xingshen　Li Wang Journal of Information Resources Management    2025, 15 (3): 108-121.   DOI: 10.13365/j.jirm.2025.03.108 Abstract （511）      PDF（pc） （5454KB）（758）       Knowledge map    Save Breakthroughs in generative artificial intelligence have led to the emergence of phenomenon-level large language models (LLMs), such as ChatGPT, posing unprecedented challenges to traditional data utility assessment methods. In response, this study focuses on evaluating the utility of instruction-tuning data for LLMs by establishing a multi-dimensional assessment framework that integrates three key dimensions—complexity, usability, and diversity—and accordingly proposes a novel data utility evaluation function. Experiments on multiple publicly available instruction-tuning datasets demonstrate that the proposed approach provides a reasonable and effective means of measuring data quality, while the reasoning loss observed in LLMs fine-tuned on different datasets exhibits a high degree of consistency with the proposed evaluation metrics. This work is the first to directly employ reasoning loss as a measure of the quality of LLM instruction-tuning data, further introducing the three dimensions—complexity, usability, and diversity—to characterize “high-quality data”. By proposing new quantitative metrics, this study offers important theoretical and practical guidance for future improvements in the quality of instruction-tuning data for large language models and related research applications. Related Articles | Metrics | Comments（0）

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Research on the Data Governance Framework for Artificial Intelligence: Construction and Prospects Based on Policy Texts Zhou Wenhong　Xiong Xiaofang　Ye Yahan Journal of Information Resources Management    2025, 15 (4): 87-98.   DOI: 10.13365/j.jirm.2025.04.087 Abstract （472）      PDF（pc） （1302KB）（151）       Knowledge map    Save To explore a data governance framework for artificial intelligence (AI), this paper aims to clarify the layout and progress of data governance actions within current global AI strategies, thereby promoting the optimization of AI policy systems in the context of digital intelligence transformation. This paper conducts a statistical analysis of AI policies released by government departments in various countries and regions, extracting policy provisions related to data governance. Using content analysis, this paper outlines a data governance framework for AI and proposes directions for optimization based on the existing framework. It is found that the current policy framework for AI-oriented data governance includes four key points: data subjects, data objects, data lifecycle management, and data security. While showing reference points, it also reflects the optimization construction direction of the data governance framework for artificial intelligence from strengthening the participation of data management institutions, highlighting the orientation of professional resource construction, supplementing key links, and optimizing phased focus configuration. Related Articles | Metrics | Comments（0）

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Data Factor Circulation Policy in the Digital Economy Era: Constitutive Elements, Theoretical Framework, and Practical Path Yan Helong　Liu Jiangfeng　Wang Ziyi　Pei Lei Journal of Information Resources Management    2025, 15 (3): 76-92.   DOI: 10.13365/j.jirm.2025.03.076 Abstract （460）      PDF（pc） （19024KB）（146）       Knowledge map    Save In the era of digital economy, data has become a key factor of production. An in-depth discussion on the constituent elements and theoretical system of data factor circulation policy can provide theoretical support for the market-oriented practice path of data factor in China at the policy level. This study combines proceduralised grounded theory and large language model to propose an automated policy text coding method with both theoretical rigor and technical advancement. By designing the coding architecture of "text slicing-analog coding-iterative integration-manual inspection-text extraction" and combining the prompt techniques such as result self-confirmation, role prompting, and thought chain, the problem of large model illusion is effectively alleviated, and the analysis efficiency is significantly improved while the coding quality is guaranteed. This method is effectively applied to data factor circulation policy, and identifies six main categories and their correlation, such as data property rights and security governance, infrastructure and technical support, data element market and its ecological construction. Then, it reveals the shortcomings of the current market development from the perspective of supply and demand, and puts forward policy suggestions on coordinating data right confirmation and data opening, improving the depth and breadth of data application, and promoting the construction of data factor market in a hierarchical and subregional manner. Related Articles | Metrics | Comments（0）

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App Walkthrough Method: A New Approach for Human Information Behavior and Interaction Design in the Era of Digital Intelligence Zhao Yuxiang　Ye Xujie　Li Jinhao Journal of Information Resources Management    2025, 15 (3): 60-75.   DOI: 10.13365/j.jirm.2025.03.060 Abstract （432）      PDF（pc） （3839KB）（810）       Knowledge map    Save In the era of digital intelligence, the proliferation of mobile applications has profoundly altered the way individuals interact with information and technology, posing challenges to the study of human information behavior and spurring the need for innovative research methods. The App Walkthrough Method, an emerging research approach, offers new opportunities and powerful tools for the investigation of human information behavior and human-computer interaction. This paper provides a systematic review of the App Walkthrough Method, sorting out the relevant research, examining in detail the evolution of the method's origin and its theoretical basis, elaborating the specific implementation steps, and analyzing in depth the research object and research theme. Furthermore, this paper proposes key areas for future research, aiming to bridge the gap between theoretical conceptualization and practical applications, and to offer a new research perspective and framework for the fields of human information behavior and user experience design. Related Articles | Metrics | Comments（0）

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Changes in International AI Evaluation Systems and Implications Wang Chenlin　Wang Chuhan Journal of Information Resources Management    2025, 15 (3): 93-107.   DOI: 10.13365/j.jirm.2025.03.093 Abstract （420）      PDF（pc） （13650KB）（119）       Knowledge map    Save The international AI evaluation systems and their index reports contain rich information, reflecting the current state of global AI technology development and practical application. They reveal the focal points of various countries' attention towards AI and their international competitiveness, making them valuable for research. This study selects the major international AI evaluation systems according to five key principles and obtains the corresponding annual index reports. Using a comparative analysis method, the study examines aspects such as the background of reports, evaluation purposes, hierarchical structure of the indicator framework, and the logic of index source, clarifying the characteristics and differences of various AI evaluation systems. Then the study analyzes the changes in the evaluation hierarchical structure and dimensions, as well as the indicator number and content, revealing the development trends of AI technology and international concerns. The findings offer targeted insights and implications for the innovation and development of AI technology, policy formulation, and enhancing global competitiveness of China. Related Articles | Metrics | Comments（0）

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A Review of the Behavioral Research on Conversational Search: Defining the Paradigm, Constructing Models, and Characterizing Behaviors Meng Gaohui　Liu Chang Journal of Information Resources Management    2025, 15 (4): 24-41.   DOI: 10.13365/j.jirm.2025.04.024 Abstract （410）      PDF（pc） （1862KB）（161）       Knowledge map    Save At the developmental turning point brought by the generative artificial intelligence (GenAI) wave, this paper provides a comprehensive review of research on conversational search behavior. It examines how the new paradigm transforms traditional perceptions of search behavior, summarizes the current state and limitations of this field, and offers valuable research directions for future studies. By reviewing the research progress in defining the overall characteristics of human-computer interaction, modeling the behavior categories and development processes of users and agents, and characterizing the behavior features and related factors of users or agents in conversational search, it argues that the main limitations of previous studies are that research objects seldom cover the cognitive and emotional activities that drive objective dialogue actions, research scenarios are mostly limited to simulated human-human dialogue scenarios, and research topics rarely involve the evaluation of user behavior performance and the enhancement of user capabilities. Future research should inherit and develop the cognitive research paradigm in the field of interactive information retrieval, expand the research scenarios to real human-computer dialogues under the GenAI scenario, and focus on evaluating and discovering better user behavior patterns. Related Articles | Metrics | Comments（0）

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Digital Interaction: A New Dimension for Analyzing Digital Inequality Zhang Yuhao　Yan Hui Journal of Information Resources Management    2025, 15 (2): 36-45.   DOI: 10.13365/j.jirm.2025.02.036 Abstract （410）      PDF（pc） （745KB）（758）       Knowledge map    Save With the rapid development of Information and Communication Technology, accelerating digital development and building Digital China is one of our country’s important development goals. Narrowing the digital divide and reducing digital poverty are key measures to achieve this goal. This study aims to develop the concept of digital interaction, thereby enriching the connotations and scope of digital inequality and advancing theoretical research on digital inequality. Based on the theoretical framework related to social support and social interaction, this study utilizes a combination of semi-structured interview methods and diary methods. Data was collected from 43 interviewees and 18 recorders through various means such as audio recordings, text, and images. The aim was to explore and analyze the manifestations of digital interaction across different age groups. The study constructed a three-dimensional theoretical framework to describe digital interaction, identifying three main categories: interaction types, ties between interaction participants, and interaction content. The interaction types encompass ten subcategories: receiving help, offering help, digital sharing, digital competition, digital cooperation, digital restriction, digital conflict, digital compliance, digital imitation, and digital exchange. The relationships between interaction participants include two subcategories: strong ties and weak ties. The interaction content comprises five subcategories: devices, networks, applications, functions, and information. This research provides a theoretical foundation for the development of subsequent measurement frameworks and explores how digital interaction influences digital inequality. The findings offer valuable insights for policymakers, researchers, and social workers in designing more effective interventions to bridge the digital divide and promote social equity. Related Articles | Metrics | Comments（0）

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Constructing a New Ecology of Information Resources Management Discipline Development Empowered by New Quality Productivity Forces Chu Jingli　Liu Jingyi　Li Nan Journal of Information Resources Management    2025, 15 (2): 13-19.   DOI: 10.13365/j.jirm.2025.02.013 Abstract （395）      PDF（pc） （654KB）（314）       Knowledge map    Save Constructing the new ecology of the development of information resources management discipline empowered by new quality productivity forces is of great significance for the high-quality development of the discipline. It is the core key to discipline construction and development. This article first analyzes 9 aspects for the information resources management discipline to understand new quality productive forces, such as new thinking, new technologies, and new methods, and advocates integrating information resources into the development of disciplines. Then, the fundamental of discipline construction is proposed, and the traditional ecology and new ecology of the discipline are discussed. Finally, it proposes the new ecological construction paths of information resources management discipline, which includes strengthening the top-level design of the discipline, adhering to the right path and innovation, striving to build a second-level discipline system, highlighting the characteristics of new liberal arts and talent training, strengthening research capabilities and scientific research and teaching output, and narrowing the gap between academia and industry. Related Articles | Metrics | Comments（0）

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A Study of Negative Rumor Diffusion in Listed Companies Based on Social Network Text Mining Guo Jianli　Wang Nan　Zhu Nanli Journal of Information Resources Management    2025, 15 (3): 152-160,封3.   DOI: 10.13365/j.jirm.2025.03.152 Abstract （390）      PDF（pc） （7756KB）（128）       Knowledge map    Save This study investigates the key factors driving rumor diffusion, traces their intertwined evolution, and analyzes the diffusion mechanisms to support listed companies in formulating effective crisis management strategies to mitigate potential losses. First, this study examines diffusion paths to identify key elements in the spread of negative rumors on social networks. Using the "Haitian double standards" incident as a case study, this research collects data from Sina Weibo and analyzes it within a life-cycle theoretical framework, employing methods such as social network analysis and LDA topic modeling. Tools like Gephi and Python are further utilized to identify key elements and trace the evolution of the diffusion network. Finally, practical crisis management strategies are proposed based on the diffusion mechanism. This study found that the three key elements in the spread of negative rumors on social networks, namely users, information content and time periods, are intertwined and evolving during the spreading process. As time progresses, user degree centrality shows an inverted U-shape. Key participants transition from grassroots, non-verified users to authoritative, verified users, and eventually back to non-verified users. Meanwhile, content themes evolve towards core issues and then transition to long-term performance, with the growth phase being a crucial period for the progression of the event. Listed companies can enhance their crisis response by targeting influential users and addressing critical content themes during this phase to proactively mitigate risks. Related Articles | Metrics | Comments（0）

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The Application of Social Science Experiment in Information Behavior Research: An Exploration of the Value of Experimental Methods Zhang Shuhan　Zhang Xiaotong　Li Yuelin Journal of Information Resources Management    2025, 15 (2): 20-35.   DOI: 10.13365/j.jirm.2025.02.020 Abstract （383）      PDF（pc） （7769KB）（165）       Knowledge map    Save The experimental method has become a significant research approach in the field of information behavior, and its academic value has been widely acknowledged. This paper analyzes the characteristics, limitations, and future directions of the experimental method in information behavior research, providing insights for its further development in this domain. The analysis focuses on literature published in SSCI and CSSCI (including the extended edition) journals, encompassing a total of 180 relevant articles. Using content analysis, the paper examines four key aspects: types of information behavior, types of experiments, experimental procedures, and research outcomes. The findings reveal a rich and long-tailed distribution of information behavior types and diverse data collection methods. However, the analysis also highlights limitations, such as the prevalence of homogeneous experimental settings and participant groups. Based on these findings, the paper proposes a framework for the application of the experimental method in information behavior research and explores future directions for experimental studies in the digital and intelligent era. Related Articles | Metrics | Comments（0）

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Exploring Factors Affecting Individual’s Social Loafing Propensity in Human-AI Collaborative Creative Task Wang Siran　Yan Qiang Journal of Information Resources Management    2025, 15 (2): 123-136.   DOI: 10.13365/j.jirm.2025.02.123 Abstract （371）      PDF（pc） （1035KB）（1412）       Knowledge map    Save Drawn on motivation theory and social cognitive theory, this study investigates the potential factors that affect individual social loafing tendency in these tasks. The findings reveal that task visibility, perceived others’ loafing tendency, and distributive justice significantly affect individuals’ social loafing tendencies when collaborating with AI. Additionally, creative self-efficacy indirectly affects social loafing tendencies through personal outcome expectation and negatively moderates the relationship between perceived others’ loafing tendency and individual social loafing tendency. These results enhance the understanding of how an individual’s social loafing tendency is affected in human-AI collaborative creative tasks and offer practical suggestions for practitioners to improve human-AI collaboration. Related Articles | Metrics | Comments（0）

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Exploration of the Five-stage Theoretical Model of Data Elementization of Cultural Heritage Sun Jing　Zhang Tong　Wang Jiandong Journal of Information Resources Management    2025, 15 (3): 37-48.   DOI: 10.13365/j.jirm.2025.03.037 Abstract （368）      PDF（pc） （1461KB）（986）       Knowledge map    Save The elementization of cultural heritage data demonstrates a positive role in stimulating the value of such data and promoting the development of the cultural industry. However, challenges such as difficulties in data rights confirmation, lack of standards, an underdeveloped market system, and inconsistent pricing logic persist throughout the elementization process. This article innovatively proposes a five-stage theoretical model for the elementization of cultural heritage data, offering insights into activating its value and facilitating the transformation and upgrading of the cultural industry. At different stages of the elementization process, it is necessary to address these challenges and promote development by building a national platform for the registration and verification of cultural heritage data property rights, formulating standards and guidelines for data product development, optimizing valuation frameworks for data assets, improving trading mechanisms, and enhancing the regulatory system for financial innovation related to cultural heritage data. Related Articles | Metrics | Comments（0）

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The Leap from Data Resources to Data Asset: Path and Prospects for the Information Resources Management Discipline Li Ying　Cao Yufei Journal of Information Resources Management    2025, 15 (3): 11-19.   DOI: 10.13365/j.jirm.2025.03.011 Abstract （363）      PDF（pc） （9129KB）（157）       Knowledge map    Save As the fifth major production factor, the key to releasing the value of data lies in its assetization. This paper finds that the leap from data resources to data asset involves five key domains: confirmation of ownership of data asset,value assessment and pricing of data asset, data asset recognition in balance sheet, circulation and trading of data asset, and governance and management of data asset. The disciplinary responsibility and mission of Information Resources Management(IRM), as well as its theoretical system centered on data and information, provide inevitability and possibility for IRM to conduct research on data assetization. Moreover, IRM has already achieved relatively complete research results in data resources management, supporting its steady progress towards data assetization. Based on this, this paper looks ahead to the future research on data assetization in IRM, pointing out that IRM scholars should strengthen systematic research on data policies and regulations and improve the framework of data asset governance system in the future; focus on the open circulation of government data assets and explore new paths for authorized management; deeply explore the content and management of data assets in public libraries, and help promote service innovation and competitiveness improvement; pay attention to characteristic entities such as data providers and third-party service providers, and expand the practice of data assetization; address the ownership and security issues of user data assets, and enhance the data literacy and ability cultivation of practitioners. Ultimately, this paper aims to promote the improvement of the data-related research system in the IRM discipline. Related Articles | Metrics | Comments（0）

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The Configurational Approach to Innovation in Technology-based Small and Medium-sized Enterprises Based on the Synergistic Framework of “Capabilities-Motivation-Policy” Wang Liuhong　Wang Hongqinling　Ba Zhichao　Wang Qi Journal of Information Resources Management    2025, 15 (3): 135-151.   DOI: 10.13365/j.jirm.2025.03.135 Abstract （359）      PDF（pc） （2605KB）（438）       Knowledge map    Save Technology-based small and medium-sized enterprises (SMEs) serve as a pivotal force in bolstering independent innovation and facilitating research transformation. Understanding how technology, market forces, and policy mix interact to influence their innovation is crucial for fostering sustainable and high-quality growth among technology-based SMEs. Given the current dearth of comprehensive discussions on multifaceted conditions and mechanisms underlying local technology-based SME innovation, this study draws the Fogg behavior model (FBM) to conceptualize the innovation process of these enterprises as a collective driving behavior jointly shaped by capabilities, motivations, and policy interventions. It introduces an integrated analytical framework to explore the innovation landscape of local technology-based SMEs and employs a dynamic fsQCA method to conduct a configuration analysis of 283 cases from urban technology-based SMEs across China between 2015 and 2022. This analysis incorporates both inter-group and intra-group comparisons to reveal the spatiotemporal distribution disparities in configuration coverage. Our results indicate that: 1)the innovation of technology-based SMEs within a city is jointly propelled by its fundamental capabilities, innovation motivations, and a combination of policy interventions; 2)the synergistic interaction of “capabilities-motivations-policy” forms five distinct configuration paths that facilitate high-level innovation among local technology-based SMEs, exhibiting notable spatiotemporal heterogeneity; 3)under conditions of strong innovation motivation, capabilities and policy intervention combinations enhance the innovation level of local technology-based SMEs through equivalent substitution, achieving similar outcomes through diverse approaches. Related Articles | Metrics | Comments（0）

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Analysis on the Differences in the Diffusion Speed of Scientific Papers and Its Influencing Factors from the Perspective of Social Media Users Hou Jianhua　Yang Siyu　Wang Yuanyuan　Zhang Yang Journal of Information Resources Management    2025, 15 (2): 151-162,封3.   DOI: 10.13365/j.jirm.2025.02.151 Abstract （354）      PDF（pc） （5238KB）（1222）       Knowledge map    Save This study aimed to develop a metric for measuring the diffusion speed of scientific knowledge on social media platforms, using Twitter as an example, and to investigate the differences between short-term and long-term diffusion speeds of scientific papers, as well as their influencing factors. Articles published in Volumes 66-68 of CA: A Cancer Journal for Clinicians were selected as the research sample. The entropy weight method was used to construct a metric for diffusion speed. SPSS was used to analyze the differences between short-term and long-term diffusion speeds, while Eviews was employed to conduct Granger causality analysis to identify the factors influencing these differences. The analysis revealed that the number of keywords and the number of authors significantly influenced the diffusion speed of scientific knowledge on social media. In the short term, the diffusion speed was Granger-caused by the citation count of the first author, whereas in the long term, it was influenced not only by citation counts but also by the first author’s academic impact, as measured by their h-index. These findings suggested that the diffusion speed of scientific knowledge on social media is affected by multiple factors. Specifically, the number of keywords and the number of authors played a significant role in both short-term and long-term diffusion. Moreover, in the short term, the citation count of the first author was a key driver, while in the long term, both citation counts and the first author’s academic impact contribute to sustained dissemination. Therefore, scholars with higher academic influence were more likely to facilitate the long-term diffusion of their scientific papers on social media, primarily through the endorsement of their academic reputation. Related Articles | Metrics | Comments（0）

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Sources of Policy: A New Mode of Policiometrics Huo Fanfan　Huo Chaoguang　Yao Yuqi Journal of Information Resources Management    2025, 15 (2): 46-58.   DOI: 10.13365/j.jirm.2025.02.046 Abstract （345）      PDF（pc） （14560KB）（141）       Knowledge map    Save Policiometrics and policy text quantification analysis play an important role in uncovering complex patterns within policies. However, existing policiometrics models are relatively simplistic and lack innovation. Drawing inspiration from the connotation and system of source of law, this paper proposes a new model called "sources of policy". Unlike the sources of law that focus solely on tracing legal sources or policy diffusion that examines the spread and adoption of policies among different levels and regions of government, sources of policy emphasize the legal basis, value foundation, ideological basis, and spiritual basis of policy formulation. It refers to the superior policies, ideological origins, related requirements, overall guidelines, or general instructions of a given policy. Based on the underlying meanings of various source of policy indicators, four primary categories are identified: citation-based source of policy, implementation-based sources of policy, application-based source of policy, and utility-adjustment-based source of policy. For the first time, a comprehensive category system comprising 17 subclasses of sources of policy is developed. An empirical analysis is conducted using local data governance policies as a case study. The findings reveal that this source of policy model effectively quantifies and analyzes policy interrelationships. Different sources of policy categories comprehensively depict the implications of their respective relationships. Using local data governance policies as an example, the model partially reflects the patterns presented by different sources of policy and source network in data governance, while also uncovering issues and deficiencies in the sources of policy of existing data governance policies. This model holds significant value in unveiling dynamic policy changes and interrelations. It is applicable across various domains, offering a new framework for policy quantification analysis research and enriching existing policy research methodologies. Related Articles | Metrics | Comments（0）

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Theoretical Framework on Synergistic Mechanism and Extraction Strategy of Scientific and Technological Knowledge Driven by Data-Intelligence Xiang Bo　Yan Zhaoping　Pan Zhuoya　Yu Dejian　Shi Jin Journal of Information Resources Management    2025, 15 (3): 122-134.   DOI: 10.13365/j.jirm.2025.03.122 Abstract （336）      PDF（pc） （3716KB）（467）       Knowledge map    Save It is the important issue to promote the value realization of data elements through clarifying the multiple stakeholders and multi-source heterogeneous data of scientific and technological knowledge, and their synergistic mechanism, as well as delineating the knowledge extraction paths empowered with big data and intelligent technology. Based on the process of data-to-wisdom derivation in the DIKW chain, this study constructed a synergistic framework of scientific and technological knowledge involving multiple stakeholders, such as universities, research institutes, enterprises, government and the public, covering multi-source data such as papers, patents, products, policies and user-generated content. Furthermore, this study expanded the front-end and back-end structures of scientific and technological knowledge extraction paths, and explored the knowledge extraction outcomes and their diverse service scenarios under intelligent strategy combination patterns. Driven by digital intelligence, scientific and technological knowledge has formed a bi-directional and multi-dimensional intertwined synergy pattern under the direction of multi-stakeholders to facilitate the interaction and matching of knowledge supply and demand. Related Articles | Metrics | Comments（0）

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Policy Changes in Digital Service Regulation: The EU’s Approach and The China’s Mirror Li Guihua　He Peipei　Huang Lin Journal of Information Resources Management    2025, 15 (2): 59-72.   DOI: 10.13365/j.jirm.2025.02.059 Abstract （336）      PDF（pc） （1951KB）（1272）       Knowledge map    Save The negative externalities of digital services on Internet platforms has attracted extensive regulatory attention. The study of the global typical EU digital service regulation policy changes can provide a mirror for China's Internet platform regulation and digital service policy. Based on the policy feedback theory, this paper constructs an analytical framework, standardizes the content and reform practice of the EU digital service regulation policy, and combs the evolution of the EU digital service regulation policy of "lenient responsibility-balanced responsibility-diligence responsibility". In this process, the regulation activities of policy change are influenced by the first order feedforward resource effect and the interpretation effect. The formation of new public policy is shaped by the evolution effect of second-order feedback and the learning effect. Based on this logic, the EU has created a policy reform approach for digital service regulation, which covers three major strategies: policy consolidation, policy learning and policy adaptation. To sum up the experience of EU digital service regulation policy is of great significance for our country to learn from EU approach scientifically and rationally. Related Articles | Metrics | Comments（0）

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Integration of Data and Traditional Production Factors: Mechanisms, Paths, and Guarantees Wu Jiang　Yuan Yiming　Miao Jiarui　Zhang Dongying　Lin Zhenyang　Du Le Journal of Information Resources Management    2025, 15 (5): 4-13.   DOI: 10.13365/j.jirm.2025.05.004 Abstract （323）      PDF（pc） （1340KB）（196）       Knowledge map    Save With the accelerated development of the digital economy, the deep integration of data elements with traditional production factors has become a key driver of industrial upgrading, as data elements ultimately realize their value in practical application scenarios. Through literature review and theoretical analysis, this study summarizes the mechanisms by which data elements interact with traditional production factors, including the multiplier effect, the entropy reduction effect of information, and the data network effect. It further explores four synergistic pathways toward all-factor integration, identified from practical application scenarios of such integration. Based on these findings, this study proposes safeguard strategies to promote the coordinated development of data elements and multiple production factors across four application dimensions: land data governance, labor skill transformation, capital allocation, and technological innovation. This study provides theoretical support for unlocking data value and constructing a modernized system of production factors. Related Articles | Metrics | Comments（0）

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Unlocking the Value of Local Chronicle Data Elements: From Formation to Realization Ding Qiujing　Zeng Jianxun Journal of Information Resources Management    2025, 15 (3): 49-59.   DOI: 10.13365/j.jirm.2025.03.049 Abstract （312）      PDF（pc） （1325KB）（381）       Knowledge map    Save Against the backdrop of China's systematic layout of the data infrastructure system, the formation and realization paths of the value of local chronicle data elements are further clarified. Based on the relevant research findings related to the development and utilization of local chronicles and the realization of data element value, this paper first articulates the connotation and characteristics of local chronicle data elements, pointing out that local chronicle data elements have the following characteristics: non-excludability of public culture, synergism of data aggregation, derivativeness of knowledge recombination, and complexity of property rights management. Secondly, it constructs a local chronicle data element value chain that covers the entire process from data collection and aggregation to data service utilization. Finally, it proposes strategies for the realization of the value of local chronicle data elements from four aspects, including top-level design, unified registration mechanism, product system construction, and the construction of a trustworthy data space. The research findings are conducive to promoting the expansion of China's local chronicle work from compilation to data production and application. They also help to stimulate the innovative vitality of local chronicles and enable them to play a greater role in the construction of Digital China, especially in the strategy of cultural digitalization. Related Articles | Metrics | Comments（0）

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Pathways to the Value Realization of Cultural Heritage Data Elements: A Three-Force-Driven Perspective Wu Yuting　Zhou Xiaoying　Chen Yanfang Journal of Information Resources Management    2025, 15 (3): 21-36.   DOI: 10.13365/j.jirm.2025.03.021 Abstract （295）      PDF（pc） （8141KB）（128）       Knowledge map    Save In order to explore the pathways to realizing the value of cultural heritage data elements, enhance the efficiency of data management and application, provide theoretical support for the digital protection and innovative utilization of cultural heritage, and provide replicable experience for relevant policy formulation and practice, this study selected 50 typical “Data Element X” projects in the cultural heritage sector and collected descriptive texts pertaining to these initiatives. Following the grounded theory methodology, the project texts were coded and analyzed, ultimately leading to the construction of a process model for value realization of cultural heritage data elements. This study finds that data management, project planning and scenario application are the key driving forces in this process. Driven by the three forces, the standardization foundation is consolidated by data management power, the dynamic integration of elements is promoted by project overall planning power, and multi-dimensional value is released by scene application power. This forms a third-order pathway of “foundation construction-element integration-value jump”, which ultimately contributes to constructing a three-dimensional value network of “core scene-derivative ecology-cultural community”. Related Articles | Metrics | Comments（0）

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Experts in Information Resource Management Discipline Discussing "The 2024-2035 Master Plan on Building China into a Leading Country in Education"(Part 2): Opportunities and Challenges for the Discipline Wang Xiaoguang Liu Yuenan Zhang Yang Journal of Information Resources Management    2025, 15 (3): 4-10.   DOI: 10.13365/j.jirm.2025.03.004 Abstract （295）      PDF（pc） （629KB）（1088）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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A Study on User’ Information Screening Ability in Interaction with Generative Artificial Intelligence: Influence Mechanisms and Cultivation Strategies Wu Dan　Guo Qingyue Journal of Information Resources Management    2025, 15 (4): 80-86.   DOI: 10.13365/j.jirm.2025.04.080 Abstract （277）      PDF（pc） （1565KB）（142）       Knowledge map    Save Against the backdrop of the rapid development of generative artificial intelligence, helping users to improve their information screening ability and construct cognitive subjectivity in interaction is essential for promoting the development of an intelligent society. From the perspectives of generative technology, cognitive subject and information system, this study identifies the challenges that users face in screening information in interaction. It then analyses both the positive and negative influence mechanism of users' information screening ability. Based on this, this study proposes strategies to cultivate AI systems, enhance users' AI literacy and optimise the interaction mechanism from a socio-technical point of view. These strategis aim to activate users' deep processing mechanisms and inhibit tendency towards processing inertia. This study provides a theoretical explanation of the influence mechanism of information screening ability in the context of human-AI interaction, supporting the formulation of strategies to cultivate users' information screening ability. Related Articles | Metrics | Comments（0）

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A Comparative Study on User Behavior and Learning Effect Between Conversational Search in AIGC Environment and Traditional Search Zhao Yiming　Yu Xinjie　Chen Yijin　Zhang Xin　Yang Yunhe Journal of Information Resources Management    2025, 15 (4): 56-71.   DOI: 10.13365/j.jirm.2025.04.056 Abstract （267）      PDF（pc） （3297KB）（777）       Knowledge map    Save This study compares the differences between generated AI supported conversational search and traditional web search in user information search behavior and learning outcomes. Combined with the cognitive load theory, this study explores the information acquisition efficiency, learning outcomes and user experience of users using the two systems in various learning search situations, aiming to deeply understand the characteristics of user information search behavior and help improve the information search and learning outcomes. The experimental method was used to collect the index data, the experimental subjects were divided into a conversational search and a traditional web search group, and the user's learning information search behavior was divided into information seek behavior, information selection behavior and information utilization behavior. The learning search outcomes were divided into five dimensions, and a linear regression model was used to compare the differences in information search behavior and learning effect between the two groups of users. Results show that users' use of conversational search system can improve the learning outcome by reducing the cognitive load, and also make part of the user's information search behavior more complex. This study provides theoretical support for revealing the cognitive mechanism behind users' information search behavior and learning outcome differences, broadens the research vision of "search as learning", and provides practical enlightenment for improving the interactive design of the functions of conservational search and traditional web search system and providing learning information service functions. Related Articles | Metrics | Comments（0）

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Research on the Influence of Initiative in Conversational Search Systems on Human-AI Collaboration Fu Shiting　Jiang Tingting　Song Defeng Journal of Information Resources Management    2025, 15 (4): 42-55.   DOI: 10.13365/j.jirm.2025.04.042 Abstract （262）      PDF（pc） （3789KB）（185）       Knowledge map    Save This study examines the role of proactivity in conversational search systems (CSS), identifying three key proactive interaction strategies, i.e., clarification, suggestion and disclosure.A mixed-initiative CSS was developed based on these strategies and compared with a user-initiative CSS. Experimental results showed that proactive CSS significantly improved the intrinsic, contextual, and representation quality of search results, enhanced system usability and social presence, and increased user trust and task attraction. Team consensus consistently mediated these effects. The findings offer both theoretical and practical insights for designing proactive CSS. Related Articles | Metrics | Comments（0）

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Beyond Text-Centrism: The Transformation of Chinese Digital Humanities Driven by Multimodal Technologies Liu Wei　Shan Rongrong　Jin Jiaqin Journal of Information Resources Management    2025, 15 (5): 14-20.   DOI: 10.13365/j.jirm.2025.05.014 Abstract （255）      PDF（pc） （677KB）（111）       Knowledge map    Save Digital humanities research has traditionally centered on textual analysis, yet this "text-centrism" paradigm reveals significant limitations within the Chinese context, including insufficient character set coverage, low OCR accuracy, and the loss of non-textual cultural information, all of which hinder a comprehensive study of China's rich material cultural heritage. The emergence of multimodal technologies offers a transformative pathway for Chinese digital humanities. This paper investigates the predicaments of text-centrism, analyzes solutions enabled by multimodal fusion technologies, and uses DeepSeek’s Janus Pro model as a case study to illustrate the potential of unified multimodal large-scale models in ancient text digitization, intelligent agent development, and cultural heritage preservation. The results show that multimodal technology can reconstruct cultural memory through cross-modal synergy, enhance the public's cultural identity, and provide technical and methodological support for the transformation of Chinese digital humanities. Related Articles | Metrics | Comments（0）

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Exploring the System and Mechanism of National Data Infrastructure for Promoting the Value Release of Data Elements Zhao Yiming　Li Linxin　Luo Lin　Wang Zizhao　Huang Dandi Journal of Information Resources Management    2025, 15 (5): 21-33.   DOI: 10.13365/j.jirm.2025.05.021 Abstract （220）      PDF（pc） （1211KB）（162）       Knowledge map    Save The national data infrastructure serves as the key carrier for the circulation and utilization of data elements throughout their entire life cycle. It plays a strategic role in promoting the aggregation, sharing, security, and efficient use of data resources. From the perspective of value release of data elements, this paper systematically analyzes the functional and institutional requirements for the national data infrastructure. It is proposed that the national data infrastructure should provide support in all stages of data elements value realization, including "creation of use value—mining of application value—release of multiple values". Furthermore, this paper constructs a three-dimensional organizational system of "region—industry—enterprise" and an operational mechanism that includes "one core, two pillars, and two safeguards." This builds a comprehensive system for the construction and operation of national data infrastructure, covering the entire data element chain across platforms and hierarchical levels. Additionally, safeguard measures for the innovation of the construction and operation system mechanism are proposed from the dimensions of technological innovation, institutional construction, and ecological collaboration. This study provides theoretical basis and practical reference for promoting the high-quality development of national data infrastructure in China and accelerating the release of data element value. Related Articles | Metrics | Comments（0）

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Research on Collaborative Training of Small and Large Language Models for Scientific Entity Extraction with Few-Shot Data Liang Zhu　Liu Yinpeng　Shi Xiang　Huang Yong　Cheng Qikai Journal of Information Resources Management    2025, 15 (4): 129-143.   DOI: 10.13365/j.jirm.2025.04.129 Abstract （200）      PDF（pc） （10557KB）（83）       Knowledge map    Save Faced with issues such as high resource consumption, long processing times, and poor scalability in scientific entity extraction tasks, this paper proposes a collaborative training framework that balances the advantages of both small and large language models. The paper tests the effectiveness of this learning framework's model training under different data scales. Using four datasets from different fields—NCBI, BC4CHEMD, S800, and SCIERC—this method is shown to achieve results consistent with full-data fine-tuning in few-shot environments. The paper provides an in-depth analysis of the limitations of large language model prediction strategies in scientific entity extraction tasks and systematically tests the model performance exhibited by small and large language models under different data scales through multiple rounds of collaborative training. Additionally, from the dual perspectives of small model recognition strategies and training data similarity, this paper thoroughly examines the reasons for the improved performance of the proposed learning framework. The collaborative training framework built in this paper enables the simultaneous exploitation of large language model cognitive advantages and small model low-cost, high-efficiency operations, thus better supporting efficient extraction of bibliometric information in low-resource, few-shot environments. Related Articles | Metrics | Comments（0）

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How Digital Government Empowers Social Governance: A Quasi-Natural Experimental Study Based on the “National Pilot Project of Information Benefiting the People” Policy Li Junrong　Liu Zhiyong　Fan Ruguo　Lu Jianfeng Journal of Information Resources Management    2025, 15 (4): 99-113.   DOI: 10.13365/j.jirm.2025.04.099 Abstract （198）      PDF（pc） （1548KB）（94）       Knowledge map    Save The construction of digital government is an important lever for promoting the modernization of governance system and governance capacity. The “National Pilot Project of Information Benefiting the People” policy is adopted as an exogenous policy shock for digital government construction, and the empirical analysis of the mechanism of digital government empowering social governance is conducted using methods such as double difference-in-differences (DID) and regression discontinuity (RD). The study found that after the implementation of the “National Pilot Project of Information Benefiting the People” policy, the level of social governance in the pilot areas has been significantly improved. The construction of digital government will promote the participation of social subjects in public affairs decision-making by improving the use of the Internet, improve the efficiency of social governance, reduce the perception of uncertainty, and amplify the social governance effect of “National Pilot Project of Information Benefiting the People”. At the same time, the impact of digital government on social governance will be restricted by factors such as policy lag effect and show significant heterogeneity. In order to continuously and efficiently empower social governance, in the future, China should promote and improve the construction of a digital government by ensuring comprehensive digital governance coverage, strengthening digital empowerment, motivating officials to take proactive actions, and enhancing public participation. Related Articles | Metrics | Comments（0）

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Technology Opportunities Identification and Evaluation Based on Policy-Technology Topic Association：A Case Study of the New Energy Vehicle Industry Zhang Zihan　Li Yang　Wu Keye Journal of Information Resources Management    2025, 15 (5): 82-98.   DOI: 10.13365/j.jirm.2025.05.082 Abstract （177）      PDF（pc） （7117KB）（82）       Knowledge map    Save Previous studies on technology opportunity identification are mostly limited to the perspective of technology itself, pay insufficient attention to policy documents that directly reflect the major strategic demands of a country. In view of this, this paper proposes a technology opportunity identification method based on policy-technology topic association, aiming to explore the potential gaps between policy demands and technological development. Specifically, this paper uses policy documents to represent policy demands and patent technologies to represent the degree of technological development. The identification of technology opportunities is divided into three modules: topic extraction of policies and technologies, topic association, and identification and evaluation of policy-technology integration opportunities. Firstly, this paper identifies policy and technology topics by constructing a LDA topic model. Then, word embedding and hierarchical clustering methods are used to establish the mapping relationship between policy and technology. This paper locates technology opportunity by constructing identification quadrant according to the identification rules. Finally, This study takes the field of new energy vehicles as an example to verify the effectiveness of research framework, which provides information support for country and research institutions to accelerate the layout in this field. Related Articles | Metrics | Comments（0）

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Logic and Framework of the Nationwide Integrated and Multifunctional Data Registration System Wang Jingxuan　Sun Zhan　Liu Qi　Yang Qianqian　Wu Jiang Journal of Information Resources Management    2025, 15 (4): 72-79.   DOI: 10.13365/j.jirm.2025.04.072 Abstract （175）      PDF（pc） （967KB）（239）       Knowledge map    Save Data registration is a foundational element in building a robust data governance system and plays a central role in regulating the emerging data element market. While local pilot initiatives for data registration are gaining momentum across China, significant differences remain in core aspects such as registration functions, target entities, validity frameworks, and institutional objectives. This paper reviews the current landscape of data registration practices and analyzes the practical demands of various stakeholders from both governmental and market perspectives. Based on this analysis, it proposes a integrated, multifunctional national data registration framework aimed at supporting data circulation and utilization, unlocking data value, and facilitating the establishment of an integrated national data market. Related Articles | Metrics | Comments（0）

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Influencing Factors of Discontinuous Usage Behavior of Mobile Short-Form Video Users: A Systematic Literature Review Dai Bao　Zheng Yiqing　Yang Liying Journal of Information Resources Management    2025, 15 (5): 131-146.   DOI: 10.13365/j.jirm.2025.05.131 Abstract （168）      PDF（pc） （1486KB）（101）       Knowledge map    Save This paper aims to explore the factors influencing the discontinuous usage behavior of mobile short-form video users, with the purpose of providing theoretical guidance for operators to develop effective user retention strategies and offering insights for deepening related studies. Based on the “Theory-Context-Methodology” (TCM) framework, the paper first systematically reviewed the research status of mobile short-form video users' discontinuous usage behavior, examining theoretical foundations, research contexts, and methodological approaches both domestically and internationally. Subsequently, it synthesized the influencing factors and mechanisms underlying this behavior by integrating the dual-factor (enabling-inhibiting) perspective, the information ecology perspective, and the S-O-R model.The present study reveals that the discontinuous usage behavior of mobile short-form video users is significantly influenced by enabling factors such as privacy concerns, information overload, system feature overload, and upward social comparison, as well as inhibiting factors including switching costs, information timeliness, platform usefulness, and social influence. Related Articles | Metrics | Comments（0）

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Topic Mining and Spatial Effect of China’s Digital Economy Policy Texts Xu Huichao　Zhao Yanyun Journal of Information Resources Management    2025, 15 (5): 51-65.   DOI: 10.13365/j.jirm.2025.05.051 Abstract （166）      PDF（pc） （4583KB）（125）       Knowledge map    Save The digital economy policy is one of the manifestations of the government's support for the development of the digital economy, and the analysis of policy characteristics is helpful to clarify the implementation effect of the policy. Based on the characteristics of the digital economy and from the perspective of the digital economy industry chain, this study uses 468 comprehensive digital economy policies in China from 2017 to 2022, combined with text analysis methods, network analysis methods and spatial econometric models. The results show that China's digital economy policies are divided into eight categories: talent training, enterprise and park development, service platform, technology development, industrial integration development, declaration and evaluation, management and planning, and rewards and subsidies. Overall, the digital economy policies have significantly promoted the development of the digital economy in both the region and neighboring regions. Policies related to talent training and technology development have shown significant positive externalities, and policies on enterprise and park development, service platforms, technology development, incentives and subsidies, and management and planning all show obvious digital economy promotion effects. The number of digital economy policies has a long-term impact on the development of the digital economy, while the intensity of digital economy policies has a significant effect in the short term. Related Articles | Metrics | Comments（0）

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A Typical Action Integrating Intelligence and Data: Data Sensemaking in User-Generated Intelligent Search Engine Interactions Peng Siyuan　Wu Siying　Ling Shang　Li Qiao　Wang Ping Journal of Information Resources Management    2025, 15 (5): 34-50.   DOI: 10.13365/j.jirm.2025.05.034 Abstract （161）      PDF（pc） （3569KB）（106）       Knowledge map    Save Generative intelligent search engines, which integrate generative artificial intelligence technology and retrieval techniques, have the potential to support researchers in overcoming challenges during data sensemaking, but they also come with certain risks. Drawing upon sense-making theory, information behavior model, information search process model, and information search behavior model, this study preliminarily proposes the Data Search As Data sensemaking(DS-DSM) theoretical model. To explore this model, this study conducts a user experiment on the Bing Copilot platform to understand how researchers construct the meaning of data through interaction with generative intelligent search engines. The findings indicate that in the interaction scenario of generative intelligent search engines, the essence of researchers’ data search is data sensemaking. This study also identifies the stages of this process and reveals how, at each stage, researchers cognitively, affectively, and behaviorally engage with generative intelligent search engines as a bridge to overcome gaps in the data sensemaking process to complete data-centered tasks. In data-related task situations, researchers’ sensemaking begins at the formulation stage. In contrast, in research-related task situations, some researchers first go through initiation, selection, and exploration stages without clear goals. In the formulation stage, the types of gaps researchers face and the bridges they use are the most diverse, showing the most complex behavioral, cognitive, and affective responses. Based on these findings, this study proposes practical strategies for optimizing the design of generative intelligent search engines and conducting user literacy education. Related Articles | Metrics | Comments（0）