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    A Review of Research on Elderly-oriented Digital Products: Demand Mining, Obstacle Analysis and Optimal Design
    Lin Yuqin Zhao Yang Liu Wanting Wang Lin
    Journal of Information Resources Management    2024, 14 (4): 146-160.   DOI: 10.13365/j.jirm.2024.04.146
    Abstract1618)      PDF(pc) (4159KB)(22777)       Save
    The "digital divide" exacerbated by the simultaneous development of population aging and social digitization has become increasingly severe, prompting a focus on the research and design of elderly-oriented digital products within both industry and academia. Using a systematic review approach, this study analyzes 348 research articles on elderly-oriented digital product design indexed in CNKI and Web of Science from 2014 to 2023. It explores the research progress and developing trend of the demand mining, usage obstacles, and optimal design of digital products for elderly users. The findings reveal that research on elderly users' needs mainly focuses on the three levels of material, emotional and spiritual needs, with significant focus on sensory barriers, cognitive barriers, behavior barriers and psychological barriers in product usage. The study investigates elderly-oriented design through various lenses, including design standards, optimization countermeasures, and usability testing. Future research should further consider the evolving nature of digital products and demographic trends by enhancing the methods for sample collection, innovating research methodologies, and expanding the content of studies. The findings of this study provide valuable references for identifying research priorities in elderly-oriented digital product adaptation, spotlighting emerging areas, advancing theoretical frameworks, and also offer practical insights for the proactive development of an age-friendly digital society.
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    The Evolution and Contemporary Perspectives on the Empowerment of Intelligence by Artificial Intelligence Technology
    Li Guangjian Pan Jiali
    Journal of Information Resources Management    2024, 14 (2): 4-20.   DOI: 10.13365/j.jirm.2024.02.004
    Abstract1839)      PDF(pc) (1976KB)(5528)       Save
    This paper systematically explores the evolution and application of artificial intelligence (AI) technology in intelligence work, revealing its new developments in ideology, characteristics, technical methods, and practical scenarios. Transitioning from a rule-based paradigm to the era of foundation model approaches, AI presents significant opportunities for the intelligence field’ s enhancement in intelligence processing. However, it also introduces novel challenges related to ethics, legal considerations, and privacy concerns. The paper identifies issues and challenges that should be addressed by the intelligence community in the new era of intelligence. Furthermore, the paper proposes forward-thinking strategies to address these issues and challenges, providing valuable insights for the stable development of intelligence field.
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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
    Abstract966)      PDF(pc) (790KB)(5332)       Save
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    Value Creation of Data Elements: Review and Research Prospects
    Zhao Caijing
    Journal of Information Resources Management    2024, 14 (2): 41-53.   DOI: 10.13365/j.jirm.2024.02.041
    Abstract2000)      PDF(pc) (985KB)(5273)       Save
    Data has become a key production factor in China’s economic and societal development, with the circulation and value realization of data elements progressively becoming a crucial means for the high-quality development of the digital economy. This paper reviews the literatures and practices concerning the value creation of data elements, examining aspects such as the connotation, mechanisms, driving factors, obstacles and development paths. Based on this, this paper identifies gaps in the existing literatures on the value creation of data elements, advocating for a future research agenda that emphasizes interdisciplinary integration. It also proposes to explore future research directions and methodologies from perspectives including the conceptualization and measurement of data element value, determinants, and mechanisms of influence.
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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
    Abstract1400)      PDF(pc) (5622KB)(5136)       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.
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    Identifying Technology Opportunities from High-Value Patents in Universities: The Case of Generative Artificial Intelligence
    Ran Congjing Li Wang Huang Wenjun
    Journal of Information Resources Management    2024, 14 (4): 103-116.   DOI: 10.13365/j.jirm.2024.04.103
    Abstract750)      PDF(pc) (2703KB)(4877)       Save
    This study proposes a method for identifying technological opportunities of high-value patents in colleges and universities, using theme modeling, mutation level method, machine learning and outlier detection algorithms to further identify technological themes and patented technologies with potential technological opportunities on the basis of evaluating high-value patents in colleges and universities. Taking the field of "Generative Artificial Intelligence" as an example for empirical evidence, the results show that the potential technology themes in the field of "Generative Artificial Intelligence" are centered on cutting-edge areas such as deep learning, neural networks and machine learning, and AI imaging and AI diagnosis and treatment are potential technological opportunities in this field, and the above technologies are vigorously supported by relevant national policies. This method can break through the core problems such as poor targeting of the identification results of a single technology opportunity identification method, low value of the identified patents, and a single form of the identification results, and the relevant identification results can provide decision-making support for the technology transfer, technology research and development, and technological innovation of universities.
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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
    Abstract982)      PDF(pc) (3124KB)(4235)       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.
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    Exploring the Generation Mechanism of Affective Responses of User Danmaku Commenting Behavior in Reaction Videos
    Ye Xujie Zhao Yuxiang Zhang Yan Li Jinhao Preben Hansen
    Journal of Information Resources Management    2024, 14 (2): 104-120.   DOI: 10.13365/j.jirm.2024.02.104
    Abstract1099)      PDF(pc) (3042KB)(3994)       Save
    Investigating the generation mechanism of affective response of danmaku commenting behavior in reaction videos can provide valuable insights into the reasons for affective generations and the process of affective change. This paper takes reaction videos of the Bilibili video website as examples. We conduct coding using the directed content analysis method by selecting the danmaku resources, video content, and reactor responses of 11 popular videos in different camps as samples. Based on the Affective Response Model (ARM), this paper builds a theoretical framework of the generation mechanism of affective responses of user danmaku commenting behavior in reaction videos. The results suggest that affective responses of user danmaku commenting behavior in reaction videos generally follows the path of "information cues-affective response", that is, information cues can arouse emotions or particular affective responses autonomously, and they can also affect the generation of emotions or learned affective responses by arousing particular affective responses. The proposed framework helps to improve the contextualized exploration of ARM theory in computer-mediated communication and will also provide practical implications for optimizing user-information interaction in social media.
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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
    Abstract1032)      PDF(pc) (2333KB)(3654)       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.
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    Research on the Model of Public Data Entering the Data Element Market
    Fan Jiajia
    Journal of Information Resources Management    2024, 14 (2): 68-81.   DOI: 10.13365/j.jirm.2024.02.068
    Abstract795)      PDF(pc) (1208KB)(3620)       Save
    Public data is an important component of the data marketplace, yet its modes of entry and participation categories have received limited attention in the current literature. This paper investigates the modes of public data participation in the data element market, both domestically and internationally, through sorting and comparative analysis. We identified two main categories and five modes for public data to enter the data element market, including: 1) the primary market (authorized operation) + secondary market (trading in the data exchange) mode, 2) the public data development and utilization + trading outside the data exchange mode, 3) the construction of a public data circulation market mode based on data platforms, 4) the trading mode using data brokers and data intermediaries, and 5) the participation in the data market mode through (public) data trusts. Building upon this categorization, the paper proposes an ideal mode for public data entry into the data element market, outlined in three phases: data acquisition, data product production, and data product trading. This paper offers insights for strategic selection regarding the entry of public data into the data element market in China.
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    A Triple Helix Coupling Model of China’s Open Government Data Resource System
    Chen Ling Jiang Guoyin
    Journal of Information Resources Management    2024, 14 (2): 121-135.   DOI: 10.13365/j.jirm.2024.02.121
    Abstract684)      PDF(pc) (4882KB)(3532)       Save
    This study delves into the intricate dynamics of open government data, examining its coupling and coordinated evolution from a systemic lens, which is pivotal for advancing the openness of government data, enhancing data value empowerment, and promoting the development of both the data industry and digital economy. This study establishes an isomorphic mapping between the theoretical model and the empirical system and constructs a triple helix model and functional equation for the open government data system, with a focus on data openness, data utilization and data value. Employing a hierarchical analytical framework that dissects the relationships among ‘element-subsystem-system’, the study provides an empirical evaluation of the data coupling intensity among the data resources available on China’s government open platforms. From the perspective of resource-based theory, this study proposes the coordination and optimization path of government data resources, which provides a new theoretical perspective and methodological support for future research of open government data.
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    The Developing Directions of Information Resources Management Discipline in the Era of Artificial General Intelligence
    Yan Hui
    Journal of Information Resources Management    2024, 14 (2): 21-28,53.   DOI: 10.13365/j.jirm.2024.02.021
    Abstract1031)      PDF(pc) (765KB)(3507)       Save
    This paper reviews the seventy-year developing history of Artificial Intelligence and Artificial General Intelligence(AGI), reflects on the fifty-year history of information resources management, analyzes the profound and multifaceted impacts of AGI on the knowledge system, education system, and career system of information resources management, and proposes three suggestions for the developing direction of information resources management discipline in the AGI era.
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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
    Abstract1130)      PDF(pc) (4448KB)(3438)       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.
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    Intelligent and Smart Service of Multi-model Cultural Heritage Resources: From Available to Evidential and Experiential
    Xia Cuijuan
    Journal of Information Resources Management    2023, 13 (5): 44-55.   DOI: 10.13365/j.jirm.2023.05.044
    Abstract1069)      PDF(pc) (2030KB)(3325)       Save
    The development of data and intelligence technologies is promoting the transformation from "digital GLAMs" to "smart GLAMs". In the transformation from digitalization to datafication and then to intelligence, the cultural heritage resources of GLAMs show the multi-model characteristics of multimedia, multi-format and multi-granularity. Aiming at the problem of how GLAMs provide intelligent services based on multmodel cultural heritage resources, this paper summarizes the transformation path of cultural heritage resources from digital, data to intelligent services based on case analysis and literature research. According to the low to high degree of resource intelligence, inteligent services can be summarized into three modes: available, evidential and experiential, which correspond to three different demand scenarios: resource-centered services, digital intelligence evidence-based services, and interactive experience-centered services. It is concluded that the intelligent services of multi-model cultural heritage resources are to predict in advance and automatically adapting to users' needs for different modes of cultural heritage resources in different demand scenarios.
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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
    Abstract620)      PDF(pc) (2258KB)(3223)       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.
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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
    Abstract712)      PDF(pc) (2456KB)(3117)       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.
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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
    Abstract592)      PDF(pc) (1784KB)(3116)       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.
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    Institute of Information Science, Shanghai Academy of Social Sciences, Shanghai, 200235
    Zhang Zhun
    Journal of Information Resources Management    2024, 14 (2): 54-67.   DOI: 10.13365/j.jirm.2024.02.054
    Abstract939)      PDF(pc) (1104KB)(3064)       Save
    The guideline, which includes twenty key measures to build basic systems for data released in December 2022 (referred to as the "Twenty Data Measures"), proposes a structural separation system for data property rights, with "incentivizing data circulation" as its core focus. The rational allocation of the right to hold data resources affects the initial distribution of data benefits, serving as the foundation for achieving the strategic goal of "common use and shared benefits" of data. Under the traditional exclusive property rights mindset, the allocation patterns of the right to hold data resources may exacerbate conflicts of interest among data co-producers. This article suggests allocating the right to hold data resources among data co-producers in a "1+N" model, which means "prior hold data right for a specific data producer + access rights for N other data producers". With the support of tools such as technical governance and transparency governance, it explores a new, fair, and efficient data property rights system that aligns with the developing laws of the data economy.
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    The Construction of Cultural Heritage Smart Data for the Inheritance and Activation
    Wang Xiaoguang Hou Xilong
    Journal of Information Resources Management    2023, 13 (5): 5-14,43.   DOI: 10.13365/j.jirm.2023.05.005
    Abstract982)      PDF(pc) (2842KB)(3034)       Save
    Smart data is becoming a new development trend of information resource construction in the age of data and intelligence. It is an advanced form of data resources organization and more suitable for the new demands and requirements on the data and service in the new environment. Firstly, this article systematically reviews the historical evolution and development trend of smart data, and analyzes the scientific meaning and critical features of smart data. Secondly, facing the problems of cultural heritage inheritance and activation, this article explains the internal logic of smart data empowering cultural heritage activation. Finally, the article puts forward the construction measures and path of cultural heritage smart data, including the construction mechanism, smart data standards and specifications, cultural gene deconstruction, quality control system. The research of smart data not only improves the quality and efficiency of big data resources, but also contributes to the theoretical reform of information resources management and knowledge management in the empowerment of data and intelligence. The construction of cultural heritage smart data resources will effectively promote the process of cultural heritage protection, inheritance and activation.
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    The Path and Empirical Study of Intelligence Support for Emergencies by Fusing Eventic Graph and Network Opinion Analysis——Taking Hazardous Chemical Accidents as an Example
    Zhang Shiying Li Yang
    Journal of Information Resources Management    2023, 13 (4): 60-71.   DOI: 10.13365/j.jirm.2023.04.060
    Abstract1129)      PDF(pc) (4153KB)(2986)       Save
    Existing emergency intelligence support has some deficiencies, such as static knowledge, fuzzy reasoning, and spatial homogeneity. The paper proposes a path of emergency intelligence support that integrates eventic graph and network opinion analysis, aiming to improve the situational awareness and predictive response capability of emergencies in complex situations, and support emergency intelligence paradigm innovation in the era of digital intelligence empowerment. The paper constructs a framework for emergency intelligence support from the integrated perspective of reasoning and knowledge fusion, business and network fusion, and carries out empirical research using hazardous chemical accidents as an illustration. The work includes building a database of relevant emergencies, portraying the development logic of emergencies using an eventic graph, and describing the impact of emergencies in cyberspace using online opinion analysis techniques. This provides intelligence support for emergency management and decision making for new emergencies. The intelligence support path proposed in this paper can take into account the characteristics of multi-source spatial data as well as the integration of event logic and knowledge, allowing for a more systematic "past-future" intelligence prediction of emergencies. The empirical study and validation of hazardous chemical accidents also show good knowledge presentation and intelligence reasoning.
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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
    Abstract710)      PDF(pc) (2994KB)(2898)       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.
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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
    Abstract607)      PDF(pc) (3045KB)(2877)       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.
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    An Empirical Study on the Influence Model of Social Media Users’ Disinformation Verification Behavior
    Mo Zuying  Liu Huan  Pan Daqing
    Journal of Information Resources Management    2023, 13 (4): 72-83.   DOI: 10.13365/j.jirm.2023.04.072
    Abstract1454)      PDF(pc) (1561KB)(2833)       Save
    This paper examines the factors and paths that affect users' information verification behavior, in order to help users avoid disinformation on the internet and achieve self-purification of cyberspace. Based on the elaboration likelihood model(ELM), this paper uses questionnaire and structural equation model to develop the influence model of social media users’ disinformation verification behavior and conducts an empirical study on the factors that affecting users’ information verification behavior. The result shows that information simulation, information topic popularity and platform trust are the key factors on users’ affective reactions, while information relevance, information topic popularity, and media richness are the key factors on users’ perception of risk. The users’ attitudes, which include emotion and cognition are the primary determinants of users’ information verification behavior. This study can provide references for the management of social media platforms and the prevention of users’ spreading disinformation.
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    Construction and Application of Semantic Interoperability Concept System from the Perspective of Standardization: Taking Development of Smart Cities International Standards as an Example
    Huang Jie An Xiaomi Kuang Miaomiao Wu Jing
    Journal of Information Resources Management    2024, 14 (3): 56-68,135.   DOI: 10.13365/j.jirm.2024.03.056
    Abstract846)      PDF(pc) (3928KB)(2812)       Save
    This paper adopts ISO 704:2022 terminology work—principles and methods, regards the definitions of “semantic interoperability” in international standards as the research objects, and then identifies the core concepts, characteristic and their relationships of “semantic interoperability”. It constructs a concept system of “semantic interoperability” based on international standards, which reveals the capability characteristics and functional requirements of “semantic interoperability”. Then, this paper uses case analysis method to map the “semantic interoperability” characteristics of relevant international standards in the field of smart cities, to analyse gaps in the development of semantic interoperability standards and to provide guidance for selection and development of semantic interoperability standards in smart cities, which helps verify the practicality of this concept system. The research has shown that this system has significance for improving efficiency of data, information, and knowledge sharing and exchange in artificial intelligence scenarios, for promoting data, information, and knowledge association, fusion, and interpretability, and for promoting standardization collaboration on multi-dimensional, multi-scenario, and multi-dimensional semantic interoperability.
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    Information Reach: Influence of the Language Expression of Disaster Warning Message
    Wang Fang Hu Qiandai Ma Xin
    Journal of Information Resources Management    2024, 14 (4): 36-51.   DOI: 10.13365/j.jirm.2024.04.036
    Abstract684)      PDF(pc) (1739KB)(2806)       Save
    In the context of natural disasters, as one of the key factors affecting the effectiveness of emergency management, the effective reach of emergency pre-warning messages is of significant value to enable the target audience to prepare in advance and mitigate disaster losses. To investigate the impact of information expression on the reach of emergency pre-warning messages, this study, based on prospect theory and reference point effect, employed an experimental research method to collect self-reported perception and behavioral data from the audience of pre-warning messages in the context of urban rainstorm disaster. The influences of the information expressions including different reference points on the effectiveness of information arrival were examined. The results indicated that information expression designed based on different reference points has different effects on the reach of disaster pre-warning messages. Specific information reference points and social comparison reference points significantly affect the audience's perception of disaster severity and risk, while the negative impact reference point does not have a significant effect. Furthermore, cognitive load affects the reach of information that contains both comprehensive reference points and specific information reference points related to disaster prevention measures. This study advances the research on information reach theory and has significant implications for improving government information expression, enhancing the effectiveness of disaster pre-warning messages delivery.
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    Assessment of Urban Data Element Market Readiness from the Perspective of Information Ecology Theory
    Gu Jie Liu Yubo Wang Zhen Tang Qifeng
    Journal of Information Resources Management    2024, 14 (2): 82-94,135.   DOI: 10.13365/j.jirm.2024.02.082
    Abstract745)      PDF(pc) (2810KB)(2724)       Save
    Building the data element market stands as a crucial foundation for the successful implementation of China's digital strategies and the development of the digital economy. China's data element market is still in its early development stage, though data resources are abundant. Recognizing the imbalanced development status is essential for both theory and practice. This paper proposes the concept of "data element market readiness" based on the nascent market characteristics. Following the "tripartite constitution" of information ecology theory, an indicator system is established to measure the market readiness of 298 Chinese cities. Spatial analysis is further conducted on inter-city balance and regional competitiveness. The results objectively reflect the current overall status, issues and regional features of China's data element market, providing implications for policy making to promote an integrated national market.
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    Research on the Motivation of Social Media Information Deletion:Take WeChat Moments as an Example
    Yu Mengli Shen Wenhan Zheng Bowen
    Journal of Information Resources Management    2023, 13 (4): 84-95,121.   DOI: 10.13365/j.jirm.2023.04.084
    Abstract1260)      PDF(pc) (2531KB)(2541)       Save
    As the amount of user-generated content grows, an increasing number of users start to delete previous posts. Information deletion in social media is not only a personal information management behavior for social media users but also has an impact on the development of social platforms content resources. Based on self-awareness theory and the perspectives of defense acquisition information management, this study investigates the motivations behind the deletion behavior of WeChat users' moments. The results of Structural Equation Modeling demonstrate that information security, field environment, and content value of defensive management have a significantly positive influence on information deletion behavior, and that the level of self-disclosure plays a mediating role in the relationships between information security, information value, and social media information deletion behavior. The research contributes to a comprehensive understanding of social media users' usage paradigm and provides decision support for the utilization of social media data and economic development of platforms.
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    Reflections on Construction of Information Resources in University Libraries Serving National Strategies in the Era of Open Science
    Huang Ruhua Shi Leyi
    Journal of Information Resources Management    2024, 14 (4): 16-28.   DOI: 10.13365/j.jirm.2024.04.016
    Abstract953)      PDF(pc) (907KB)(2484)       Save
    The arrival of the open science era has changed the information environment and scholarly communication system, and has also brought new opportunities and challenges to the construction of information resources in university libraries. Based on the national strategies of becoming a leading country in education, science and technology, talent, culture and so on, construction of information resources in Chinese university libraries urgently needs to achieve high-quality development on the basis of serving multiple national strategies. This article proposes countermeasures in four aspects, including: constructing information resources that are consistent with a holistic approach to national security, constructing information resources system needed for the digitalization of Chinese higher education, consolidating the information resource foundation for great self-reliance and strength in science and technology, and strengthening information resource support needed for construction of philosophy and social sciences with Chinese characteristics.
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    The Impact of Regional Technical Criticality and Genericness on Industrial Innovation Performance: A Case Study of the Fuel Cell Vehicle Industry
    Li Yue Ma Yaxue Sun Jianjun
    Journal of Information Resources Management    2024, 14 (4): 117-132.   DOI: 10.13365/j.jirm.2024.04.117
    Abstract572)      PDF(pc) (5542KB)(2371)       Save
    This study investigated the effect of regional technical criticality and genericness on the industrial innovation performance. The findings offer valuable insights for guiding targeted industrial innovation, refining technological development strategies, and optimizing resource allocation. This study took the Chinese Fuel Cell Vehicle industry as the example and represented technical units using 4-digit IPC codes and constructed a multi-layer co-occurrence network that focuses on various segments of the industry chain. This framework enabled the development of metrics to measure technical criticality and genericness, capturing the intricacies of regional technical characteristics. Regional technical advancements were subsequently assessed both temporally and spatially using provincial panel data from China spanning 2010 to 2021.
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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
    Abstract852)      PDF(pc) (5326KB)(2338)       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.
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