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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 （338）      PDF（pc） （790KB）（3881）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Research on Large Language Model Evaluation for the Generation Task of Natural Language Processing in Classical Chinese Zhu Danhao　Zhao Zhixiao　Zhang Yiping　Sun GuangYao　Liu Chang　Hu Die　Wang Dongbo Journal of Information Resources Management    2024, 14 (5): 45-58.   DOI: 10.13365/j.jirm.2024.05.045 Abstract （612）      PDF（pc） （3124KB）（2723）       Knowledge map    Save The rapid development of large language models (LLMs) presents both opportunities and challenges for their evaluation. While evaluation systems for general-domain LLMs are becoming more refined, assessments in specialized fields remain in the early stages. This study evaluates LLMs in the domain of classical Chinese, designing a series of tasks based on two key dimensions: language and knowledge. Thirteen leading general-domain LLMs were selected for evaluation using major benchmarks. The results show that ERNIE-Bot excels in domain-specific knowledge, while GPT-4 demonstrates the strongest language capabilities. Among open-source models, the ChatGLM series exhibits the best overall performance. By developing tailored evaluation tasks and datasets, this study provides a set of standards for evaluating LLMs in the classical Chinese domain, offering valuable reference points for future assessments. The findings also provide a foundation for selecting base models in future domain-specific LLM training. 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 （335）      PDF（pc） （1784KB）（2562）       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 （161）      PDF（pc） （3045KB）（2344）       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 （586）      PDF（pc） （4448KB）（2135）       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 （296）      PDF（pc） （2456KB）（1986）       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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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 （678）      PDF（pc） （5622KB）（1766）       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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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 （287）      PDF（pc） （2994KB）（1730）       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 （483）      PDF（pc） （2333KB）（1564）       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 （178）      PDF（pc） （1589KB）（1271）       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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An Exploration of the Data Assetization Paths for the Three Major Types of Data Ma Feicheng　Sun Yujiao　Xiong Siyue　Wang Wenhui Journal of Information Resources Management    2024, 14 (5): 4-13.   DOI: 10.13365/j.jirm.2024.05.004 Abstract （827）      PDF（pc） （6613KB）（1138）       Knowledge map    Save Data assetization is a key stage in grasping digital opportunities, realizing the value of data, and promoting the digital transformation of the economy and society. This paper argues that public data, enterprise data and personal data are the major subjects of data elements. However, current research on the realization path of data assetization for the three major types of data is insufficient, hindering the release of the value of data elements. In this paper, we systematically review the relevant concepts of data assets, and delve into the path of data assetization from the three major data subjects: public, enterprise and individual. The results shown that public data can serve internal government needs or be supplied to the society, generating social benefits or economic benefits through sharing and opening, and authorized operation, thus forming public data assets. Enterprises, depending on whether they hold data ownership, can carry out different degrees of processing and handling of data, so as to complete the deep excavation of data value and redistribution of data benefits, forming inventory, intangible assets and other types of data assets. The practice related to personal data assetization is limited, mainly relying on two paths: direct transaction between suppliers and demanders or entrusted transaction by data intermediaries to complete market circulation and form personal data assets. Through in-depth exploration of this topic, this study aims to provide theoretical guidance and practical reference for the value realization of data elements and the effective allocation of data resources. Related Articles | Metrics | Comments（0）

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A Study on Automatic Categorization of the Siku Quanshu Based on a Large Language Model Zuo Liang　Zhao Zhixiao　Wang Dongbo Journal of Information Resources Management    2024, 14 (5): 23-35.   DOI: 10.13365/j.jirm.2024.05.023 Abstract （398）      PDF（pc） （2258KB）（1135）       Knowledge map    Save The craze of ancient book research and the contemporary requirement of ancient book revitalisation have raised higher requirements for automatic classification of ancient books. This study explores the classification effect of Xunzi large language series models on the automatic classification of ancient books by combining the large language model along the current preface with the 25 categories of corpus from the history and scripture sections of the Siku Quanshu as the input corpus.Through the comparison experiments with its base model, the results show that Xunzi large language models for ancient books have obvious advantages in the automatic classification task of ancient books, among which the Xunzi-Baichuan2-7B large language model has the most significant advantage in the automatic classification task of ancient books, and the overall classification F1 value reaches 96.90%. In addition, the experiments of adjusting the training data size show that the Xunzi-Baichuan2-7B large language model is able to achieve comparable classification results with the base model with only a small amount of data. Therefore, the automatic classification model for ancient books based on Xunzi large language models for ancient books proposed in this study can achieve efficient fine-grained classification of ancient books and opens up a new way for the classification of ancient books in resource-constrained contexts. 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 （245）      PDF（pc） （2326KB）（1105）       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 （345）      PDF（pc） （4852KB）（1058）       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 （91）      PDF（pc） （1951KB）（1015）       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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Research on Online Public Opinion Guidance and Control of Major Emergencies from the Perspective of Actor Network：Analysis Based on the Hybrid Method of SD and fsQCA Li Ming　Hou Tiantian Journal of Information Resources Management    2024, 14 (5): 104-115.   DOI: 10.13365/j.jirm.2024.05.104 Abstract （428）      PDF（pc） （5326KB）（972）       Knowledge map    Save The occurrence of major emergencies often leads to a surge in online public opinion, making the effective guidance and control of such opinions a significant challenge in current public opinion management. From the perspective of actor-network theory, this study constructs an analysis framework for guiding and controlling online public opinion, which includes actors such as events, media, netizens, and government. A system dynamics model is employed to simulate the mechanism of online public opinion guidance and control for major emergencies. Through sensitivity analysis, the key influencing factors are identified. Based on this, the fuzzy set qualitative comparative analysis (fsQCA) method is applied to analyze the conditions configuration to explore effective pathways for online public opinion guidance and control in major emergencies. This study reveals that the severity of the event, the intensity of media coverage, the emotional intensity of netizens, and the level of government attention play crucial roles in guiding public opinion. It is essential to further strengthen the ability to analyze complex influencing factors, emphasize the roles of media and netizen actors, and enhance the organic linkage and effective collaboration between government attention and various actors to ultimately achieve effective guidance and control of online public opinion in major emergencies. Related Articles | Metrics | Comments（0）

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Data Production: Concepts, Scenarios, Technologies and Reflections Hu Guangwei　Fan Zhaoyuan Journal of Information Resources Management    2024, 14 (5): 14-21.   DOI: 10.13365/j.jirm.2024.05.014 Abstract （442）      PDF（pc） （3318KB）（930）       Knowledge map    Save Digital transformation offers significant opportunities for the development of the economy and society while also presenting numerous challenges. Issues such as the source of data, continuous supply, cultivation of core data capabilities, and the urgent need to explore data production scenarios and technologies await discussion. By discussing the concept, structure, characteristics, scenarios, and technologies of data production, we hope to draw the attention of both the theoretical and practical sectors to the new business forms of data production, promote the development of new productive forces such as digitalization, intelligentization, and wisdomization, and serve the modernization of China’s digital transformation and governance capabilities. 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 （120）      PDF（pc） （1035KB）（891）       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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Minutes of the 6th(2024) Annual Conference on E-commerce and Digital Innovation He Chaocheng　Yuan Yiming　Chen Haodong　Wu Jiang Journal of Information Resources Management    2024, 14 (5): 159-164,封3.   DOI: 10.13365/j.jirm.2024.05.159 Abstract （173）      PDF（pc） （749KB）（850）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Research on the Copyright Dilemma and Solution Path of Generative Artificial Intelligence Using Previous Works Liu Zubing Journal of Information Resources Management    2024, 14 (5): 147-158.   DOI: 10.13365/j.jirm.2024.05.147 Abstract （572）      PDF（pc） （859KB）（821）       Knowledge map    Save The rapidly development and embedded applications of generative artificial intelligence pose challenges to the existing copyright system. Generative artificial intelligence normalizes the crawling of massive amounts of prior work data, inducing infringement risks. Long distance text semantic understanding ability is intended to cover up infringement traces, and open cross domain generalization reasoning ability provides technical convenience for infringement. In terms of data feeding in works, generative artificial intelligence may cross the boundaries of fair use systems or lead to the extreme of unprotected or overprotected rights in previous works; In terms of copyright-ability of generated content, generative artificial intelligence decouples copyright subjectivity with its high-quality and massive generation ability, meeting the "minimum creative standards" and originality requirements. Propose to establish an endorsement system for the use of prior works to address the problem of rational use of algorithms; Promote the horizontal transition from "author centrism" to "work centrism", and shift the author's rights law starting from personality rights to copyright law starting from property rights; Establish an interpretable generative artificial intelligence originality evaluation mechanism and reinterpret originality standards. Related Articles | Metrics | Comments（0）

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The Influence of Information Presentation on the Persuasive Effect of Health-related Rumor Debunking Information Zhang Min　Han Xiqing　Shao Jing　Yan Weiwei Journal of Information Resources Management    2024, 14 (5): 132-146.   DOI: 10.13365/j.jirm.2024.05.132 Abstract （329）      PDF（pc） （1201KB）（798）       Knowledge map    Save Health-related rumors in social media under the failure of traditional “gatekeeper” mechanism face the problem of “rumor debunking-reappearing". Focusing on the characteristics of health-related rumors with mixed truths and emotions to explore the persuasive effect of health debunking information, this research provides a better understanding of the debunking information designing and provides useful reference for optimizing rumor management strategies. This research focuses on information presentation, through a 2 (Presentation content: one-sided content vs. double-sided content) ×2 (Presentation form: serious vs. humorous) ×2 (Rumor type: fear vs. hope rumor) online control experiment to analyze their influence on the persuasive effect of health-related rumor debunking information. Presentation content has significant influence on the persuasive effect of health-related rumor debunking information. One-sided (vs. double-sided) debunking information is more persuasive. Rumor type moderates the interaction effect of presentation content and presentation form on the persuasive effect. For hope rumors, it is better to use double-sided and humorous information or one-sided and serious information. 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 （391）      PDF（pc） （1268KB）（787）       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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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 （279）      PDF（pc） （741KB）（764）       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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Research on Algorithm Embedding and Visibility Mechanism：A Platform Affordance Perspective Du Yan　Xie Xinzhou Journal of Information Resources Management    2024, 14 (5): 91-103.   DOI: 10.13365/j.jirm.2024.05.091 Abstract （581）      PDF（pc） （4260KB）（745）       Knowledge map    Save Given the increasing relevance of algorithms, how to implement the main responsibility of platforms has become a focal issue. Based on the perspective of affordance theory, the study analyzes the relationship between algorithms, the platform environment, and user perception through mixed research methods to clarify the role of platforms in the process and the problems that arise. The research results show that the algorithm reshapes the platform environment through specific encoding programs, multi-objective optimization, and billions of feature vector combinations. For ordinary users, the algorithm is invisible, uneditable and inaccessible. The platform initially constructs the visibility mechanism of the algorithm through interface cues, but the effect is limited. The research, combined with the embedding logic of the algorithm, provides policy recommendations to promote user algorithmic knowledge, which has certain theoretical and practical significance. 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 （261）      PDF（pc） （6300KB）（721）       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 （499）      PDF（pc） （1088KB）（662）       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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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 （209）      PDF（pc） （5021KB）（661）       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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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 （281）      PDF（pc） （4793KB）（630）       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 （282）      PDF（pc） （1437KB）（618）       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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Induced Consent Analysis of Privacy Policy Based on Grounded Theory and Machine Learning Chen Menglei　Luo Yingjia　Zhu Hou Journal of Information Resources Management    2024, 14 (5): 75-90.   DOI: 10.13365/j.jirm.2024.05.075 Abstract （250）      PDF（pc） （4271KB）（586）       Knowledge map    Save Analyzing privacy policies from the user’s perspective to understand the tendency for induced consent is beneficial in helping users identify unfair terms and providing regulatory authorities with guidance to standardize app privacy policies. This study uses grounded theory to examine the tendency of induced consent in privacy policies from the user’s perspective and develops a coding system for such tendencies. After manually annotating the corpus, we trained a K-BERT model using semi-supervised learning to achieve the automated identification of statements with a tendency to induce consent within privacy policies. Moreover, further network analysis and sequence pattern mining were conducted to explore the characteristics and underlying patterns of user consent induction in privacy policies. Empirical analysis reveals that user opportunity costs, privacy management costs, and fuzzy concepts are central to the network of inducing dimensions. Fuzzy concepts and responsibility-shifting statements play a crucial role in the patterned inductive writing of privacy policies, usually appearing densely following other unfair statements. Furthermore, the study identifies significant differences in the features of induced consent between the children's domain and other domains. Some common features exist among privacy policies across specific domains, potentially linked to similarities in service delivery and business logic. Related Articles | Metrics | Comments（0）