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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 （526）      PDF（pc） （790KB）（4717）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Trends and Future Prospects in Sentiment Analysis of Financial Reviews Texts Wu Jiang　Duan Yiqi Journal of Information Resources Management    2025, 15 (1): 86-101.   DOI: 10.13365/j.jirm.2025.01.086 Abstract （881）      PDF（pc） （5622KB）（2988）       Knowledge map    Save This study surveys recent advancements in sentiment analysis of financial review texts, both domestically and internationally, to delineate the field’s developmental trajectory. Adopting dual perspectives of technology-driven and content-driven approaches, it scrutinizes prevailing research trends. Technologically, the evolution from lexicon-based methods, through traditional machine learning, to deep learning paradigms is summarized. Content-wise, BERTopic and LLaMA3 are employed for document clustering based on scholarly viewpoints, with dynamic topic modeling elucidating domain progress. Findings indicate a domestic transition from sentiment analysis methods to investigations of emotional impacts on financial market prediction. Meanwhile, international research continues progressing deep learning applications while revealing emerging interests in financial sentiment modeling. By integrating these observations, the paper proposes future directions including: (1)constructing high-quality datasets, (2)conducting granular sentiment analysis of financial discourse, and (3)improving the interpretability of analytical outcomes. These recommendations aim to establish methodological foundations for subsequent studies in this field. Related Articles | Metrics | Comments（0）

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Construction of Chinese Classical-Modern Translation Model Based on Pre-trained Language Model Wu Mengcheng　Liu Chang　Meng Kai　Wang Dongbo Journal of Information Resources Management    2024, 14 (6): 143-155.   DOI: 10.13365/j.jirm.2024.06.143 Abstract （386）      PDF（pc） （1784KB）（2933）       Knowledge map    Save This study aims to construct and validate a Chinese ancient-modern translation model based on pre-trained language models, providing strong technical support for the research of ancient Chinese and the inheritance and dissemination of cultural heritage. The study selected a total of 300,000 pairs of meticulously processed parallel corpora from the "Twenty-Four Histories" as the experimental dataset and developed a new translation model—Siku-Trans. This model innovatively combines Siku-RoBERTa(as the encoder) and Siku-GPT(as the decoder), designed specifically for translating ancient Chinese, to build an efficient encoder-decoder architecture. To comprehensively evaluate the performance of the Siku-Trans model, the study introduced three models as control groups: OpenNMT, SikuGPT, and SikuBERT_UNILM. Through comparative analysis of the performance of each model in ancient Chinese translation tasks, we found that Siku-Trans exhibits significant advantages in terms of translation accuracy and fluency. These results not only highlight the effectiveness of combining Siku-RoBERTa with Siku-GPT as a training strategy but also provide important references and insights for in-depth research and practical applications in the field of ancient Chinese translation. 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 （225）      PDF（pc） （3045KB）（2690）       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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A Multinational Comparative Study of Regulatory Policies for Generative AI from the Perspective of “Tools-Structure” Deng Shengli　Ding Weiwei　Wang Fan　Wang Haowei Journal of Information Resources Management    2025, 15 (1): 54-68.   DOI: 10.13365/j.jirm.2025.01.054 Abstract （694）      PDF（pc） （4448KB）（2448）       Knowledge map    Save Based on the dual perspective of policy tools and structural characteristics, this study takes the regulatory policies of generative AI in different countries as the research object, aiming to explore the structural characteristics and internal connections of the policy elements of generative AI, in order to promote the healthy development of generative AI. A total of 14 effective policy texts were collected, and 327 relevant text units were coded and interpreted using bibliometrics, content analysis, and BERTopic. The structural characteristics were analyzed from three dimensions: policy issuance time, policy issuance subject, and policy theme characteristics. The role paths were discussed by dividing into three types of policy tools: environmental, demand-driven, and supply-driven. The findings show that the regulation of generative AI is still in its infancy, and there are significant differences in the overall characteristics of policies among different countries, with significant differences in the regulatory level. Overall, the role path of policy tools is mainly dominated by the indirect role of environmental policy tools, showing a structural imbalance and bias in the role path. Further comparison of the similarities and differences in regulatory policies among different countries is conducted, and corresponding countermeasures and suggestions are put forward to optimize the policy tool structure, balance the role path of policy tools, assessing the effectiveness of policy implementation, and promote the coordinated development of the generative AI regulatory system. Related Articles | Metrics | Comments（0）

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A Study on the Correlation Factors of Psychological Resilience and Impact on AIGC Users’ Dropout Behavior Based on ISM-MICMAC Xie Jing　Zhang Hai　Shi Qin Journal of Information Resources Management    2025, 15 (1): 126-138.   DOI: 10.13365/j.jirm.2025.01.126 Abstract （408）      PDF（pc） （2456KB）（2378）       Knowledge map    Save In order to clarify the influencing factors of user dropout behavior in the context of AIGC, improve the user experience and willingness to continue using AIGC, and promote the high-quality development of domestic AIGC application platforms, this study drew on the grounded theory research paradigm and extracted causal factors of AIGC user dropout behavior through coding analysis of interview sample data. Based on the interpretative structural model, the intrinsic logic and correlation paths of causal factors of AIGC user dropout behavior were explored. Furthermore, the dependencies and driving forces between individual factors were studied using the cross-impact matrix multiplication method in order to identify the key factors influencing the dropout behavior of AIGC users.The research results show that psychological resilience, technological factors, perceived risk factors，and environmental factors are important factors affecting the dropout behavior of AIGC users. At the same time, it was found that psychological resilience can effectively alleviate the negative factors such as technological burden, technological risk, and information overload, and has important theoretical and practical significance for improving the sustained use behavior of AIGC users. At last, effective measures and suggestions have been proposed to resolve the dropout behavior of AIGC users and promote their continued use. Related Articles | Metrics | Comments（0）

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Measuring the Academic Value of Scientific Papers by Integrating Innovation and Recognition—A Case Study in the Field of Artificial Intelligence Wu Jiachun　Dong Ke　Chen Xingyuan　Chen Lifang　Sun Jiaming Journal of Information Resources Management    2024, 14 (6): 17-30.   DOI: 10.13365/j.jirm.2024.06.017 Abstract （358）      PDF（pc） （2994KB）（2251）       Knowledge map    Save The full text of papers and their citation relationships convey a significant amount of academic information, which helps characterize the connotation of academic value and improve the precision of value assessment. This study builds a new evaluation index of academic value based on the epistemology of value, integrating the factual knowledge based on the papers themselves with the contingent knowledge based on external citations, and selecting papers in the field of artificial intelligence from the Web of Science database from 1990 to 2021 as the experimental data. Compared with traditional metrics, the academic value measurement proposed in this study comprehensively considers the value of internal innovation(represented by innovativeness), external recognition value(based on citation sentiment, citation intensity, and citation similarity). The results showed that:(1) value of internal innovation was not correlated with either the number of citations or the number of mentions;(2) value of external recognition was positively correlated with the number of mentions but not significantly correlated with the number of citations;(3) and academic value was positively correlated with the number of mentions, value of internal innovation, and value of external recognition, although value of external recognition was not significantly correlated with value of internal innovation. The results revealed that the impact indicator based on the number of citations has a lag and is insufficient to reflect the paper’s innovation. Compared to citation counts, the number of mentions, incorporating citation preference, shows slight improvement in measuring value of external recognition. The academic value measure proposed in this study has certain advantages in integrating the internal and external values of the paper and reflecting comprehensive academic value. Related Articles | Metrics | Comments（0）

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Generation AI in Human-AI Interaction: Origins, Characteristics and Future Prospects Xu Hao　Cheng Qingxuan　Dong Jing　Wu Dan　Tian Li Journal of Information Resources Management    2025, 15 (1): 13-20.   DOI: 10.13365/j.jirm.2025.01.013 Abstract （612）      PDF（pc） （2333KB）（2220）       Knowledge map    Save The rapid development of artificial intelligence is driving society toward a new era of human-AI interaction (HAII) and reshaping a new generation of minors growing up with AI—Generation AI. This paper reviews the origins and evolution of human-computer interaction (HCI), examining the shift from HCI to HAII, and focuses on the unique traits of Generation AI in this context. By analyzing the interaction modes and characteristics of Generation AI, the study reveals their distinctive attributes in HAII scenarios, including intelligent perception, social contention, and digital embedding across all settings, timeframes, and environments. Finally, the paper envisions the future of human-AI synergy for Generation AI from three perspectives: human-centered design, multimodal interaction, and augmented collaboration, providing a theoretical foundation for building a smart and human-centered society. 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 （266）      PDF（pc） （1589KB）（1549）       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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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 （365）      PDF（pc） （2326KB）（1343）       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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Research on Theoretical Framework of Breakthrough Paper Identification Based on Citation Perspective Huang Heng　Wang Xuefeng　Chen Hongshu　Lei Ming Journal of Information Resources Management    2024, 14 (6): 31-44.   DOI: 10.13365/j.jirm.2024.06.031 Abstract （414）      PDF（pc） （4852KB）（1255）       Knowledge map    Save No consensus has been reached on the characteristics of breakthrough papers and the theoretical models for their identification. The content analysis method is adopted to analyze the similarities and differences between the characteristics of breakthrough papers and breakthrough research. A conceptual model of breakthrough paper identification is constructed from citation perspective and reflects the impact of breakthrough paper on the citation network and mainstream theories. On this basis, a breakthrough paper generation model is proposed. The influence of knowledge recombination on the originality of breakthrough papers is discussed from backward citation perspective. On the other hand, a breakthrough paper diffusion model is proposed to sort out the different paths of scientific impact cross-domain diffusion of breakthrough papers from forward citation perspective. It is found that breakthrough papers may not necessarily have all the characteristics of breakthrough research. The core characteristics consist of a huge influence on scientific research, challenging mainstream theories and interdisciplinary. The study defines the core characteristics of breakthrough papers. The conceptual model, generation model and diffusion model of breakthrough papers identification are constructed to provide a theoretical basis for the subsequent breakthrough paper identification research. 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 （145）      PDF（pc） （1951KB）（1193）       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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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 （185）      PDF（pc） （1035KB）（1146）       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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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 （176）      PDF（pc） （629KB）（1014）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Thirty Years of the Internet in China: Formation and Development of Internet with Chinese Characteristics Xie Xinzhou　Zhang Jingyi Journal of Information Resources Management    2025, 15 (1): 21-29.   DOI: 10.13365/j.jirm.2025.01.021 Abstract （325）      PDF（pc） （741KB）（974）       Knowledge map    Save This article systematically reviews the evolution of the Internet in China over the past 30 years, elucidating the exploration, formation, and development of the Internet development path with Chinese characteristics. China has adhered to an inclusive and symbiotic Internet development philosophy, forming a diverse and balanced Internet system and embarking on a uniquely Chinese way of Internet governance. Key characteristics of the Chinese Internet, such as technology-driven initiatives and industrial innovation, have become significant manifestations of this unique path. The paper summarizes the achievements and contributions of the Chinese Internet while also pointing out the major challenges China faces in the future. It aims to provide beneficial references for the high-quality development and innovative of the Chinese Internet. Related Articles | Metrics | Comments（0）

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A Study on the Impact of Team Diversity on the Innovation Diffusion of Papers in the Field of Artificial Intelligence from Causal Inference Perspective Tang Xuli　Li Xin Journal of Information Resources Management    2024, 14 (6): 45-59.   DOI: 10.13365/j.jirm.2024.06.045 Abstract （320）      PDF（pc） （6300KB）（944）       Knowledge map    Save We divided innovation diffusion in AI into two situations: whether adopted(in ten years) and continuous adoption(rapid growth period, slow growth period, and adoption saturation period) from the perspective of citation. Then, we explored the causal effects of team diversity on innovation diffusion at different stages by analyzing approximately 1.7 million AI co-authored papers using causal inference methods. We discovered that: ①the national diversity of co-author teams has positive causal effect on both whether adopted and adoption and continuous adoption. It would increase the likelihood of adoption by 7.041% to 9.818% over ten years and increase the continuous adoption by 8.082% to 16.834%. ②the team diversity across disciplines and topics has a positive causal effect on adoption and it would increase the likelihood of adoption by 3.651% to 4.697%, and by 3.052% to 5.095% over ten years, respectively. ③ the team diversity across affiliation has positive causal effect on continuous adoption and it would increase the continuous adoption by 13.506% to 18.679%. Related Articles | Metrics | Comments（0）

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The Inherent Attributes of Artificial Intelligence Generated Content(AIGC) and Its Impact on the Discipline of Information Resources Management Zhu Yu　Chen Guanze　Ye Jiyuan Journal of Information Resources Management    2024, 14 (6): 60-72.   DOI: 10.13365/j.jirm.2024.06.060 Abstract （626）      PDF（pc） （1088KB）（899）       Knowledge map    Save The inherent attributes of the concept of Artificial Intelligence Generated Content(AIGC) remains a matter of contention within the field of library and information science/ information resources management(IRM). As the issue is closely related to the core research content of IRM research, delving into this problem is significant to understand the key research areas of the discipline, with a focus on AIGC research and a moderate expansion of the disciplinary scope. This study utilized both conceptual and comparative analysis methods to investigate the inherent attributes of AIGC and its related concepts, analyzing the information resources characteristics of AIGC from three perspectives, namely, knowledge philosophy, practical needs, and disciplinary construction, thus proving the necessity of incorporating AIGC into IRM research. Moreover, this study demonstrated the rationality through an analysis of AIGC’s source technology and an examination of the information chain, leading to a renewed understanding within the framework of IRM. Notably, this study clearly identified the inherent attribute of AIGC as the value of information resources, which is one of the core research content of IRM discipline. Additionally, it presented 6 pressing research topics on AIGC for the field of IRM to address. Related Articles | Metrics | Comments（0）

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The Theoretical Logic and Implementation Path of Digital Industrialization Ma Feicheng　Wang Chunyang Journal of Information Resources Management    2024, 14 (6): 4-16.   DOI: 10.13365/j.jirm.2024.06.004 Abstract （501）      PDF（pc） （1268KB）（895）       Knowledge map    Save Digital industrialization is the core foundation of the digital economy, exerting profound impacts on both the economy and society. This paper first reviews the concepts and measurement methods of digital industrialization and explores its logical development path. Technological innovation and application have transformed the structure and distribution of data, information, and knowledge, leading to the creation of distinctive products and services, which in turn foster the formation of digital industrial chains and clusters. Moreover, digital industrialization integrates with traditional industries, driving their transformation and upgrading. The emergence of new quality productive forces presents significant opportunities for the qualitative transformation of digital industrialization. Building on this foundation, the paper proposes implementation paths for advancing digital industrialization: leading the development of digital infrastructure through "new infrastructure" initiatives, strengthening core technology research and development through original and disruptive technologies, unlocking the potential of data resources through market-oriented reforms in data elements, ensuring a steady supply of digital talent through an improved talent cultivation and recruitment system, fostering digital industrial clusters led by strategic emerging industries, promoting the deep integration of digital industrialization with the real economy through the digital transformation of traditional industries, and unleashing new momentum for digital industrialization by constructing a comprehensive digital industrial ecosystem. This study offers insights into deepening the understanding of digital industrialization and advancing reforms in this critical field. Related Articles | Metrics | Comments（0）

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Linking Allusion Words in Ancient Poetry from the Perspective of Knowledge Reorganization: A Method of Integrating the Fine-grained Co-citation Relationships and the Semantic Features Li Xiaomin　Wang Hao　Bu Wenru1　Zhou Shu Journal of Information Resources Management    2024, 14 (6): 131-142.   DOI: 10.13365/j.jirm.2024.06.131 Abstract （314）      PDF（pc） （4793KB）（850）       Knowledge map    Save Guided by theories and technologies related to knowledge reorganization, this study conducts semantic mining and organization of allusion cultural resources to promote the inheritance and utilization of allusion culture. A model is proposed that integrates fine-grained co-reference relations and semantic features to link allusion terms. First, a co-reference network is constructed based on the citation relationships between ancient poems and allusion terms, and fine-grained co-reference relations, including positional co-reference and emotional co-reference, are added to build a fine-grained co-reference network. Then, Doc2vec is employed to extract the semantic features of each allusion term, and these features are integrated to reconstruct the co-reference network. Finally, a link prediction algorithm is applied to traverse the fine-grained co-reference network, achieving semantic association and organization of allusion terms. The association results are further analyzed from a path-based perspective, uncovering some regular patterns in domain knowledge. The constructed co-reference network consists of 5,869 nodes and 27,032 edges. The proposed method, which incorporates positional and emotional co-references as well as semantic features, achieves an accuracy of 0.963 in the task of linking allusion terms. Moreover, the analysis reveals that the shortest path order is negatively correlated with both the number of allusion term pairs and their similarity. Related Articles | Metrics | Comments（0）

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Analysis on the Construction and Characteristics of Data Governance and Policy Curriculum in iSchools iCaucus Abroad Liang Shuang　Zhou Qingshan Journal of Information Resources Management    2025, 15 (1): 30-41.   DOI: 10.13365/j.jirm.2025.01.030 Abstract （330）      PDF（pc） （1437KB）（823）       Knowledge map    Save This study investigates and analyzes data governance and policy curriculum in iSchools iCaucus abroad, and summarizes the teaching contents and characteristics, so as to provide reference for the construction of related courses and talent cultivation models in China. By conducting online research, the course information and syllabuses are obtained. The study summarizes the teaching contents and constructs a framework for course classification by using content analysis, and then analyzes the teaching conditions. The findings reveal that data governance and policy courses abroad are mainly divided into five categories: management and governance, ethics and morality, policy and law, security and assurance, and comprehensive category. These courses exhibit systematic and diverse characteristics in terms of teaching objectives, prerequisites, course materials, teaching and assessment methods. Finally, this paper puts forward some suggestions on the improvement of related courses and the optimization of the teaching models in China from the aspects of curriculum system, course content and course teaching. Related Articles | Metrics | Comments（0）

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A Study on the Standardization of WeChat Mention Metrics Based on Relative Citation Methods Li Longfei　Yu Houqiang　Yang Siluo Journal of Information Resources Management    2024, 14 (6): 99-115.   DOI: 10.13365/j.jirm.2024.06.099 Abstract （298）      PDF（pc） （3527KB）（810）       Knowledge map    Save The standardization of altmetrics indicators is a crucial requirement for their application in scientific evaluation. This study targets the construction of a Chinese indigenous knowledge system, which focuses on WeChat mention data from Chinese academic papers. We used standardization methods based on relative citation methods and incorporated the WeChat Communication Index to establish standardized metrics for WeChat mentions. This research aims to provide relevant references and foundations for the development, deepening, and application of Chinese altmetrics data sources. Key findings include:(1) By eliminating time differences, disciplinary variations, high sparsity, and skewed distributions in WeChat mention metrics, the standardized indicators for WeChat mentions can be considered for application in academic evaluation and social impact assessment.(2) Within the WI(WeChat Index) journal set, philosophy and humanities, engineering II, and agricultural engineering are the top three disciplines with the highest number of WeChat mentions of academic papers.(3) WPP/FWSm and MNWS, metrics based on WeChat mention frequency, show minimal differences. These two indexes are suitable for evaluating WeChat attention at the level of individual papers and journals but are unsuitable for evaluating universities due to their influence by the distribution characteristics of WeChat mentions.(4) Standardized metrics, WCPP/FWSm and MNWC, incorporating WeChat influence indices, show a better balance between WeChat influence and mention volume. They demonstrate robustness and prove valuable for assessing WeChat attention at the individual paper, journal, and university levels. They are more effective in assessing the WeChat attention and the dissemination impact of academic papers in universities. 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 （327）      PDF（pc） （5021KB）（801）       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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Research on Local Policies in China for Data Rights Confirmation and Registration from the Perspective of Enterprise Data Assetization Wang Qin　Huang Youzhi　Wang Youwen Journal of Information Resources Management    2024, 14 (6): 85-98.   DOI: 10.13365/j.jirm.2024.06.085 Abstract （263）      PDF（pc） （6270KB）（796）       Knowledge map    Save Data ownership registration is a necessary procedure for enterprise data capitalization.This study takes seventeen local policy documents in China as research samples, sorts out and compares their application conditions, registration effectiveness, registration objects, and registration objects. After analyzing possible bottlenecks of the documents, the article proposes that enterprises cannot complete data ownership confirmation through a single registration. They need to go through three stages of registration preparation, technical certification, and rights registration to gradually confirm the ownership of data resources, data processing and use rights, and data product management rights at the technical and legal levels, so that relevant data can meet the recognition conditions of intangible assets or inventory, and achieve data asset accounting and reporting. 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 （171）      PDF（pc） （5238KB）（786）       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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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 （173）      PDF（pc） （1461KB）（783）       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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Research on New Quality Productive Forces Driving High-Quality Development of Digital Economy Ma Feicheng　Sun Yujiao　Xiong Siyue Journal of Information Resources Management    2025, 15 (1): 4-12.   DOI: 10.13365/j.jirm.2025.01.004 Abstract （776）      PDF（pc） （1353KB）（682）       Knowledge map    Save New quality productive forces, emerging from a new wave of scientific and technological revolution and industrial transformation, align with China's domestic strategic blueprint and the practical needs arising from international competitive dynamics. With digital economy becoming a pivotal force in global economic and social transformation, promoting its high-quality development has become a strategic imperative for China's economic development in the new era. This research investigates how new quality productive forces drive the high-quality development of digital economy, which holds significant implications for advancing productivity theory, understanding digital era development patterns, and facilitating economic transformation. The study first explored the evolutionary context of new quality productive forces, systematically examined its theoretical underpinnings from three dimensions of "newness," dual implications of "quality," and intrinsic characteristics of "productive forces," and analyzed its practical features. Building upon this foundation, the research revealed from a theoretical perspective how new quality productive forces drive the high-quality development of digital economy, identifying three inherent mechanisms: new technology stimulated new growth drivers, new elements reshaped production relations, and new industries reconstructed competitive landscape. Finally, the research proposed five implementation paths: improving institutional supply, strengthening talent cultivation, unleashing element value, promoting coordinated regional development, and deepening opening up. This study aims to provide theoretical guidance and practical insights for promoting the high-quality development of digital economy. 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 （242）      PDF（pc） （5454KB）（647）       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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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 （237）      PDF（pc） （745KB）（617）       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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Scientific Paper Recommendations with User Dynamic Preferences: A Knowledge Graph Approach Based on Attention Embeddings Liu Ya　Mao Qian’ang　Yan Jiaqi　Chen Xi Journal of Information Resources Management    2025, 15 (1): 113-125.   DOI: 10.13365/j.jirm.2025.01.113 Abstract （527）      PDF（pc） （2167KB）（571）       Knowledge map    Save Scientific paper recommendation systems serve as an effective solution to the problem of information overload in academic databases. This study proposes a knowledge-graph-based method employing attention embeddings for the task of scientific paper recommendation to enhance the effectiveness of recommendations. This method initially constructs a collaborative knowledge graph to integrate user behavior with paper attribute information and optimizes node vector representations using the TransR approach. Subsequently, it introduces an attention sequence module that employs an attention propagation mechanism to learn node features and utilizes a sequence attention mechanism to capture the temporal preferences of users from their reading sequences. Finally, the model calculates match scores between researchers and candidate papers to generate personalized recommendation lists. Experiments conducted on a dataset provided by the "Blockchain Laboratory" have validated the effectiveness of the model. Experimental results indicate that the proposed model significantly improves recommendation recall rates, capturing the dynamic interests of researchers more accurately. This study not only enhances the performance of scientific paper recommendation systems but also provides new perspectives and tools for understanding and predicting the evolution of researcher interests. Related Articles | Metrics | Comments（0）

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A Measurement Model for Industrial Technology Involution Index：Empirical Evidence from Strategic Emerging Industries in Shandong Province Guo Rui　Dong Kun　Tian Changwei　Chen Kexin Journal of Information Resources Management    2025, 15 (1): 102-112.   DOI: 10.13365/j.jirm.2025.01.102 Abstract （299）      PDF（pc） （2713KB）（525）       Knowledge map    Save With the continuous intensification of industrial technology competition, some industries show obvious trends of repeated innovation and technological convergence, the leading and breakthrough of technological innovation are weakened, and industrial technological progress is slowed down. In order to actively cope with this trend of "involution", it is urgent to make a scientific evaluation of the current degree of industrial technology involution. Firstly, this study clarified the connotation and characteristics of industrial technology involution. Then, we constructed a measurement model based on five dimensions of technological growth, technological difference, technological leadership, technological breakthrough and technological expansiveness to measure the degree of industrial technology involution. Finally, we selected the strategic emerging industries in Shandong Province for empirical study, measuring their technological involution index and analysing the reasons. The model can effectively measure the degree of industrial technology involution and provide a quantitative and process method model for the measurement of industrial technology involution. Related Articles | Metrics | Comments（0）