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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 （1426）      PDF（pc） （5622KB）（6484）       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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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 （1356）      PDF（pc） （6613KB）（2391）       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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Identification, Evolution, and Prospects of Global Information Literacy Education Research Themes in 1974—2024 Huang Ruhua　Wu Yingqiang　Shi Leyi Journal of Information Resources Management    2025, 15 (4): 4-22.   DOI: 10.13365/j.jirm.2025.04.004 Abstract （1304）      PDF（pc） （5120KB）（779）       Knowledge map    Save The year 2024 marks the 50th anniversary of the introduction of the term information literacy on a global scale. This study applies the BERTopic topic modeling method to identify 44 major research topics in global information literacy education over the past five decades. These topics are categorized into five thematic clusters: (1) pedagogical practices in information literacy education, (2) information literacy education driven by digital and intelligent technologies, (3) information literacy education targeting specific populations, (4) disciplinary applications of information literacy education, and (5) social and ethical issues in information literacy education. Five key topics are highlighted: librarian-faculty collaboration in higher education, nurses’ information literacy, health information literacy, teachers’ ICT competence and skill development, and information literacy in the context of artificial intelligence. By tracking topic-specific keywords, this study outlines five stages in the evolution of research: the conceptual dissemination stage, the technological impact stage, the connotation expansion stage, the convergence of multiple literacies stage, and the stage influenced by major societal events. Over the past 50 years, three prominent characteristics have shaped the development of global information literacy education research: (1) consistent focus on higher education and academic libraries across all stages; (2) a distinct phase-based impact of technology on information literacy education; and (3) the influence of changing educational environments on the content and form of information literacy instruction. Finally, six future directions are proposed for global research and practice in information literacy education: strengthening theoretical study of information literacy education, emphasizing the development of standards and assessment systems, diversifying the contexts for information use, enhancing the roles of both the academic library community and the information industry, fostering nationwide collaboration, and boosting China’s international influence in the field. Related Articles | Metrics | Comments（0）

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Research on New Quality Productive Forces Driving High-Quality Development of Digital Economy Ma Feicheng　Sun Yujiao　Xiong Siyue Journal of Information Resources Management    2025, 15 (1): 4-12.   DOI: 10.13365/j.jirm.2025.01.004 Abstract （1257）      PDF（pc） （1353KB）（1324）       Knowledge map    Save New quality productive forces, emerging from a new wave of scientific and technological revolution and industrial transformation, align with China's domestic strategic blueprint and the practical needs arising from international competitive dynamics. With digital economy becoming a pivotal force in global economic and social transformation, promoting its high-quality development has become a strategic imperative for China's economic development in the new era. This research investigates how new quality productive forces drive the high-quality development of digital economy, which holds significant implications for advancing productivity theory, understanding digital era development patterns, and facilitating economic transformation. The study first explored the evolutionary context of new quality productive forces, systematically examined its theoretical underpinnings from three dimensions of "newness," dual implications of "quality," and intrinsic characteristics of "productive forces," and analyzed its practical features. Building upon this foundation, the research revealed from a theoretical perspective how new quality productive forces drive the high-quality development of digital economy, identifying three inherent mechanisms: new technology stimulated new growth drivers, new elements reshaped production relations, and new industries reconstructed competitive landscape. Finally, the research proposed five implementation paths: improving institutional supply, strengthening talent cultivation, unleashing element value, promoting coordinated regional development, and deepening opening up. This study aims to provide theoretical guidance and practical insights for promoting the high-quality development of digital economy. Related Articles | Metrics | Comments（0）

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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 （1180）      PDF（pc） （2326KB）（1655）       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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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 （1159）      PDF（pc） （4448KB）（3631）       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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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 （1057）      PDF（pc） （2333KB）（4314）       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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Research and Design of General Knowledge Model of Ancient Books Chen Tao　Zhao Xiaofei　Yang Xin　Lin Lixin Journal of Information Resources Management    2025, 15 (1): 139-153.   DOI: 10.13365/j.jirm.2025.01.13 Abstract （1053）      PDF（pc） （8021KB）（253）       Knowledge map    Save China boasts a vast collection of ancient books. While the traditional organization and management mode of ancient books has facilitated the transformation of ancient book resources from "collection" to "use", the "raw resources" are increasingly unable to meet the needs of ancient book utilization in the digital era. This paper investigates and analyzes the reusable ontology model for ancient book knowledge organization, reviews the perspectives and approaches to knowledge modeling of ancient books, and proposes a five-layer framework for a general knowledge model of ancient books based on the two dimensions of form and content characteristics. To verify the usability of the model, this paper takes the "Hu Zi Book" of the Yongle Encyclopedia as an example, constructs an associated dataset, explores the knowledge graph of ancient books by integrating associated data, and realizes the combination of knowledge association and data aggregation.This paper constructs a general knowledge organization model for ancient books, providing an alternative approach for the association and aggregation, inference and calculation, dissemination and sharing, and intelligent application of ancient book knowledge. 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 （1022）      PDF（pc） （4260KB）（1675）       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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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 （998）      PDF（pc） （3124KB）（4542）       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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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 （986）      PDF（pc） （790KB）（5419）       Knowledge map    Save 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 （957）      PDF（pc） （1088KB）（1345）       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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Scientific Paper Recommendations with User Dynamic Preferences: A Knowledge Graph Approach Based on Attention Embeddings Liu Ya　Mao Qian’ang　Yan Jiaqi　Chen Xi Journal of Information Resources Management    2025, 15 (1): 113-125.   DOI: 10.13365/j.jirm.2025.01.113 Abstract （906）      PDF（pc） （2167KB）（1001）       Knowledge map    Save Scientific paper recommendation systems serve as an effective solution to the problem of information overload in academic databases. This study proposes a knowledge-graph-based method employing attention embeddings for the task of scientific paper recommendation to enhance the effectiveness of recommendations. This method initially constructs a collaborative knowledge graph to integrate user behavior with paper attribute information and optimizes node vector representations using the TransR approach. Subsequently, it introduces an attention sequence module that employs an attention propagation mechanism to learn node features and utilizes a sequence attention mechanism to capture the temporal preferences of users from their reading sequences. Finally, the model calculates match scores between researchers and candidate papers to generate personalized recommendation lists. Experiments conducted on a dataset provided by the "Blockchain Laboratory" have validated the effectiveness of the model. Experimental results indicate that the proposed model significantly improves recommendation recall rates, capturing the dynamic interests of researchers more accurately. This study not only enhances the performance of scientific paper recommendation systems but also provides new perspectives and tools for understanding and predicting the evolution of researcher interests. Related Articles | Metrics | Comments（0）

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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 （883）      PDF（pc） （5021KB）（1293）       Knowledge map    Save The widespread application of generative artificial intelligence (Generative AI) has brought unique privacy challenges to human-computer interaction. This study focuses on privacy disclosure in the interaction between users and Generative AI, combining large language models with manual coding to identify common types of privacy disclosed in the interaction between users and Generative AI. Based on contextual integrity theory, this study employs user annotation and semi-structured interviews to explore the mechanisms influencing user privacy disclosure. The findings reveal that user privacy disclosure is jointly affected by the user's privacy attitude, technology trust, and privacy risk perception, and the system's data management transparency indirectly affects privacy disclosure by affecting technology trust. Based on the research results, this study constructs a multi-factor influence model of privacy disclosure in the interaction between users and Generative AI, providing a theoretical reference for the development of more privacy-friendly Generative AI. Related Articles | Metrics | Comments（0）

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Research on 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 （867）      PDF（pc） （5326KB）（2770）       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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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 （832）      PDF（pc） （859KB）（1241）       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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How does the Quality of Online Health Information Trigger Cyberchondria? Multiple Mediating Roles of Perceived Uncertainty and Health Anxiety Jin Yan　Zhang Xiaohan　Sun Zhuo　Bi Chongwu Journal of Information Resources Management    2024, 14 (6): 156-169.   DOI: 10.13365/j.jirm.2024.06.156 Abstract （778）      PDF（pc） （1601KB）（657）       Knowledge map    Save In the era of "digital health", there has been a significant increase in the public's behavior of "Internet self-diagnosis" based on online health information. The uncertainty in the quality of online health information has heightened health anxiety and led to the emergence of cyberchondria. Understanding the impact of online health information quality on cyberchondria can offer valuable insights for improving online health information governance. This study investigates the mechanisms through which argument quality and source credibility affect cyberchondria from the perspective of online health information quality. We collected 386 valid responses through a questionnaire survey and performed data analysis and model testing with SmartPLS software. The results indicate that both the argument quality and source credibility significantly enhance users' perceived uncertainty and health anxiety, which are common factors contributing to the cyberchondria. Additionally, perceived uncertainty and health anxiety mediate the relationship between argument quality, source reliability, and cyberchondria. Furthermore, health anxiety serves as a mediator in the relationship between perceived uncertainty and cyberchondria. 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 （775）      PDF（pc） （1589KB）（2546）       Knowledge map    Save In the age of digital intelligence, conflicts in data ethics arising from the exploitation and utilization of data have become increasingly pronounced, challenging societal governance structures and value systems. Research on data ethics has thus emerged as a shared concern across multiple disciplines. This paper adopts a systematic review method to analyze relevant literature, synthesizing data ethics theories and summarizing the core issues in data ethics research. Current studies demonstrate a clear trend toward interdisciplinary integration, with data ethics governance practices embedded across diverse digital contexts. Both theoretical and practical dimensions exhibit characteristics of multidisciplinarity and multi-contextuality. However, there remains significant scope to enhance the systematic, comprehensive, collaborative, and normative aspects of data ethics research. Future studies could explore three key directions: effectively linking empirical and normative research on data ethics, advancing interdisciplinary integration in data ethics studies, and transitioning from context-specific applications to holistic research addressing broader data governance ecosystems. Related Articles | Metrics | Comments（0）

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The 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 （749）      PDF（pc） （1268KB）（1830）       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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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 （743）      PDF（pc） （2994KB）（3322）       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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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 （736）      PDF（pc） （2456KB）（3821）       Knowledge map    Save In order to clarify the influencing factors of user dropout behavior in the context of AIGC, improve the user experience and willingness to continue using AIGC, and promote the high-quality development of domestic AIGC application platforms, this study drew on the grounded theory research paradigm and extracted causal factors of AIGC user dropout behavior through coding analysis of interview sample data. Based on the interpretative structural model, the intrinsic logic and correlation paths of causal factors of AIGC user dropout behavior were explored. Furthermore, the dependencies and driving forces between individual factors were studied using the cross-impact matrix multiplication method in order to identify the key factors influencing the dropout behavior of AIGC users.The research results show that psychological resilience, technological factors, perceived risk factors，and environmental factors are important factors affecting the dropout behavior of AIGC users. At the same time, it was found that psychological resilience can effectively alleviate the negative factors such as technological burden, technological risk, and information overload, and has important theoretical and practical significance for improving the sustained use behavior of AIGC users. At last, effective measures and suggestions have been proposed to resolve the dropout behavior of AIGC users and promote their continued use. Related Articles | Metrics | Comments（0）

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Measuring Policy Responsiveness with Multi-dimensional Text Features：Evidence from Science and Technology Talent Evaluation Policies Lin Xi　Dong Yu Journal of Information Resources Management    2025, 15 (1): 69-85.   DOI: 10.13365/j.jirm.2025.01.069 Abstract （717）      PDF（pc） （12392KB）（228）       Knowledge map    Save Policy responsiveness reflects national governance capabilities and governance levels. This study applies political system theory as an analytical framework, integrating the subject, time, quantity, and hierarchical characteristics of opinion texts and policy texts. It extracts four indicators-response rate, response effectiveness, response enthusiasm, and response efficacy-and develops a policy responsiveness measurement model. The analysis calculates the policy responsiveness in the field of scientific and technological talent evaluation in China from 2002 to 2022. By examining themes, it identifies the development and changing characteristics of policy responsiveness and uses the theme of "How to Evaluate" as a case study to explore the specific content of policy responses. The findings demonstrate that the policy responsiveness measurement model quantifies policy responsiveness effectively and reveal a shift in China's evaluation of S&T talents from selective responsiveness to comprehensive responsiveness, and from delayed responsiveness to high-quality responsiveness. This study enriches the methods for measuring policy responsiveness, reduces the influence of subjective factors, and enhances both the theoretical depth and practical application of the research. Related Articles | Metrics | Comments（0）

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Government Data Openness Level Measurement, Regional Difference Decomposition and Dynamic Evolution：Evidence from 21 Provinces Gao Fan　Xu Sijia　Li Yiheng Journal of Information Resources Management    2024, 14 (5): 59-74,90.   DOI: 10.13365/j.jirm.2024.05.059 Abstract （716）      PDF（pc） （5908KB）（653）       Knowledge map    Save This study delves into the overall differences, regional differences, and dynamic evolution trends of interprovincial government data openness in China, with the aim of narrowing these differences, promoting balanced development in government data openness, and accelerating the digital transformation of government. Based on the Chinese Government Data Openness Evaluation Reports, the study employs the panel entropy method to calculate the comprehensive index of government data openness and four sub-dimensional indices across 21 provinces. Additionally, the study utilizes the Dagum Gini coefficient and Kernel Density Estimation to analyze the regional differences and evolution trends of government data openness across different regions. The findings reveal that the level of government data openness in China is on the rise, with significant and gradually widening regional differences. The differences across the four sub-dimensions vary, and except for the western region, the absolute differences between the eastern and central regions are expanding. This study innovatively applies the Gini coefficient to the theme of government data openness and equilibrium and integrates the entropy method, Dagum Gini coefficient, and Kernel density estimation to provide a progressive and comprehensive analysis of the overall differences, regional disparities, and future evolution dynamics of government data openness. 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 （711）      PDF（pc） （1201KB）（1960）       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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Research on Intelligent Information Processing of Ancient Books under the Large Language Model: Constituent Elements, Framework System, and Practical Path Zhang Hai　Zhao Xue　Wang Dongbo Journal of Information Resources Management    2024, 14 (5): 36-44.   DOI: 10.13365/j.jirm.2024.05.036 Abstract （710）      PDF（pc） （919KB）（1091）       Knowledge map    Save With the rapid advancement of large language models (LLMs), there is growing potential for their integration into the intelligent information processing of ancient books. This study seeks to bridge the gap between LLMs and the field of ancient books processing, enhancing the theoretical and technical foundations of the information resource management discipline. Drawing on a coding-based deconstruction method, this study analyzed interviews from 28 domain experts to identify the key factors necessary for effective integration. The analysis reveals a comprehensive framework that centers on four critical dimensions: policy, technology, ancient books, and users. Building on this framework, this study proposes a set of practical paths tailored to the unique demands of the discipline. The findings suggest that these four dimensions are essential to the successful application of LLMs in the domain. Finally, this study offers detailed strategies for implementation across theoretical, technical, and user service, providing a roadmap for future development in this emerging field. Related Articles | Metrics | Comments（0）

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Driving Factors and Mechanism of Online Reverse Social Emotion in Emergencies: A csQCA Analysis Based on 30 Cases Wang Zhongyou Journal of Information Resources Management    2024, 14 (5): 116-131.   DOI: 10.13365/j.jirm.2024.05.116 Abstract （700）      PDF（pc） （1347KB）（906）       Knowledge map    Save This study explores the driving factors and evolutionary mechanisms of online reverse social emotions during emergencies. Utilizing the Qualitative Comparative Analysis (QCA) method, this study applies the theoretical model of amplified propagation of online reverse social emotions to examine thirty emergency cases across three dimensions: netizens, media, and government. The findings indicate that there are eight configurations that exacerbate online reverse social emotions across these three dimensions. Five key factors, such as expression appeal, social equity, continuous reporting, government intervention, and concealment, play critical roles in the evolution of online reverse social emotions. The degree of emergency, mass conformity, opinion leaders, type of media, launch platform, quality of response, and level of government, when combined with key factors, can determine the direction of the evolution of online reverse social emotions. To mitigate online reverse social emotions, it is essential to ensure open channels for expressing appeal, protect the interests of netizens, strengthen media oversight to harness its value-driven role, and fulfill government emergency responsibilities to demonstrate social justice and fairness, thereby severing the pathway for online risks to translate into offline conflicts and preventing social unrest. Related Articles | Metrics | Comments（0）

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Structural Characteristics and Optimization Paths of Data Element Market Policy Text from the Perspective of Policy Instruments Zhao Xuyao　Ji Xiangfei　Zhang Jieni Journal of Information Resources Management    2024, 14 (6): 73-84.   DOI: 10.13365/j.jirm.2024.06.073 Abstract （690）      PDF（pc） （2105KB）（625）       Knowledge map    Save This paper conducts an analysis of local government data element market policy texts in China, aiming to provide theoretical support for the design of China’s data infrastructure system at the policy aspect. The study utilizes policy instruments to construct a two-dimensional framework for analyzing data element market policies based on the four principles outlined in the "Data Twenty". A cross-analysis is performed on 116 locally published policy texts related to the data element market published from 2019 to 2024 in China, revealing their structural characteristics and proposing optimization paths. The research identifies that current data element market policies exhibit features such as excessive use of environmental policy instruments, imbalanced structure systems of policy instruments, uneven utilization of these instruments with respect to policy principles, lack of coordination among internal tool combinations, and inadequate supporting facilities. Consequently, recommendations are made to strengthen supply-push and demand-pull forces, emphasize data property rights and income distribution considerations, leverage precise guidance from policy principles, and enhance ecological system construction for effective application of these policies. Related Articles | Metrics | Comments（0）

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Research on the Data Governance Framework for Artificial Intelligence: Construction and Prospects Based on Policy Texts Zhou Wenhong　Xiong Xiaofang　Ye Yahan Journal of Information Resources Management    2025, 15 (4): 87-98.   DOI: 10.13365/j.jirm.2025.04.087 Abstract （652）      PDF（pc） （1302KB）（897）       Knowledge map    Save To explore a data governance framework for artificial intelligence (AI), this paper aims to clarify the layout and progress of data governance actions within current global AI strategies, thereby promoting the optimization of AI policy systems in the context of digital intelligence transformation. This paper conducts a statistical analysis of AI policies released by government departments in various countries and regions, extracting policy provisions related to data governance. Using content analysis, this paper outlines a data governance framework for AI and proposes directions for optimization based on the existing framework. It is found that the current policy framework for AI-oriented data governance includes four key points: data subjects, data objects, data lifecycle management, and data security. While showing reference points, it also reflects the optimization construction direction of the data governance framework for artificial intelligence from strengthening the participation of data management institutions, highlighting the orientation of professional resource construction, supplementing key links, and optimizing phased focus configuration. Related Articles | Metrics | Comments（0）

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Evaluation of Prompt Fine-Tuning Data Efficacy in Large Language Models： A Focus on Data Quality Liu Xiaohui　Ran Congjing　Liu Xingshen　Li Wang Journal of Information Resources Management    2025, 15 (3): 108-121.   DOI: 10.13365/j.jirm.2025.03.108 Abstract （652）      PDF（pc） （5454KB）（859）       Knowledge map    Save Breakthroughs in generative artificial intelligence have led to the emergence of phenomenon-level large language models (LLMs), such as ChatGPT, posing unprecedented challenges to traditional data utility assessment methods. In response, this study focuses on evaluating the utility of instruction-tuning data for LLMs by establishing a multi-dimensional assessment framework that integrates three key dimensions—complexity, usability, and diversity—and accordingly proposes a novel data utility evaluation function. Experiments on multiple publicly available instruction-tuning datasets demonstrate that the proposed approach provides a reasonable and effective means of measuring data quality, while the reasoning loss observed in LLMs fine-tuned on different datasets exhibits a high degree of consistency with the proposed evaluation metrics. This work is the first to directly employ reasoning loss as a measure of the quality of LLM instruction-tuning data, further introducing the three dimensions—complexity, usability, and diversity—to characterize “high-quality data”. By proposing new quantitative metrics, this study offers important theoretical and practical guidance for future improvements in the quality of instruction-tuning data for large language models and related research applications. Related Articles | Metrics | Comments（0）

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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 （649）      PDF（pc） （3318KB）（1239）       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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A Measurement Model for Industrial Technology Involution Index：Empirical Evidence from Strategic Emerging Industries in Shandong Province Guo Rui　Dong Kun　Tian Changwei　Chen Kexin Journal of Information Resources Management    2025, 15 (1): 102-112.   DOI: 10.13365/j.jirm.2025.01.102 Abstract （648）      PDF（pc） （2713KB）（760）       Knowledge map    Save With the continuous intensification of industrial technology competition, some industries show obvious trends of repeated innovation and technological convergence, the leading and breakthrough of technological innovation are weakened, and industrial technological progress is slowed down. In order to actively cope with this trend of "involution", it is urgent to make a scientific evaluation of the current degree of industrial technology involution. Firstly, this study clarified the connotation and characteristics of industrial technology involution. Then, we constructed a measurement model based on five dimensions of technological growth, technological difference, technological leadership, technological breakthrough and technological expansiveness to measure the degree of industrial technology involution. Finally, we selected the strategic emerging industries in Shandong Province for empirical study, measuring their technological involution index and analysing the reasons. The model can effectively measure the degree of industrial technology involution and provide a quantitative and process method model for the measurement of industrial technology involution. Related Articles | Metrics | Comments（0）

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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 （634）      PDF（pc） （2258KB）（4208）       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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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 （625）      PDF（pc） （3045KB）（2899）       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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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 （618）      PDF（pc） （1784KB）（3302）       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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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 （597）      PDF（pc） （4852KB）（1830）       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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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 （586）      PDF（pc） （741KB）（1940）       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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The Identification and Application of Theories in Inter-organizational Information Sharing Research Zhou Lihong　Hu Jiangfeng Journal of Information Resources Management    2025, 15 (1): 42-53.   DOI: 10.13365/j.jirm.2025.01.042 Abstract （585）      PDF（pc） （3220KB）（590）       Knowledge map    Save Inter-organizational information sharing(IIS) research is becoming a topic of great interest to organizations and researchers around the world. The introduction of different theoretical perspectives is crucial to exploring the problems that exists in IIS. Based on a survey of the research literature closely related to IIS, this paper has identified 19 specific theories appearing in the literature which can be categorized into four perspectives in terms of game, information resource, relationship, and tension respectively. Additionally, this paper further summarizes the thematic distribution characteristics of the theories used in this research field, which are roughly focusing on four aspects: barriers, influencing factors, realization paths, and mechanisms of action. Besides, the research team constructs a system of IIS research topics and theoretical application. Finally, according to the current status of IIS theory application, future research directions are proposed. The findings of this research provide reference and guidance for systematically grasping the theoretical system composition of IIS research and the hot topics in the field. Related Articles | Metrics | Comments（0）

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Data Factor Circulation Policy in the Digital Economy Era: Constitutive Elements, Theoretical Framework, and Practical Path Yan Helong　Liu Jiangfeng　Wang Ziyi　Pei Lei Journal of Information Resources Management    2025, 15 (3): 76-92.   DOI: 10.13365/j.jirm.2025.03.076 Abstract （562）      PDF（pc） （19024KB）（225）       Knowledge map    Save In the era of digital economy, data has become a key factor of production. An in-depth discussion on the constituent elements and theoretical system of data factor circulation policy can provide theoretical support for the market-oriented practice path of data factor in China at the policy level. This study combines proceduralised grounded theory and large language model to propose an automated policy text coding method with both theoretical rigor and technical advancement. By designing the coding architecture of "text slicing-analog coding-iterative integration-manual inspection-text extraction" and combining the prompt techniques such as result self-confirmation, role prompting, and thought chain, the problem of large model illusion is effectively alleviated, and the analysis efficiency is significantly improved while the coding quality is guaranteed. This method is effectively applied to data factor circulation policy, and identifies six main categories and their correlation, such as data property rights and security governance, infrastructure and technical support, data element market and its ecological construction. Then, it reveals the shortcomings of the current market development from the perspective of supply and demand, and puts forward policy suggestions on coordinating data right confirmation and data opening, improving the depth and breadth of data application, and promoting the construction of data factor market in a hierarchical and subregional manner. Related Articles | Metrics | Comments（0）

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App Walkthrough Method: A New Approach for Human Information Behavior and Interaction Design in the Era of Digital Intelligence Zhao Yuxiang　Ye Xujie　Li Jinhao Journal of Information Resources Management    2025, 15 (3): 60-75.   DOI: 10.13365/j.jirm.2025.03.060 Abstract （557）      PDF（pc） （3839KB）（1380）       Knowledge map    Save In the era of digital intelligence, the proliferation of mobile applications has profoundly altered the way individuals interact with information and technology, posing challenges to the study of human information behavior and spurring the need for innovative research methods. The App Walkthrough Method, an emerging research approach, offers new opportunities and powerful tools for the investigation of human information behavior and human-computer interaction. This paper provides a systematic review of the App Walkthrough Method, sorting out the relevant research, examining in detail the evolution of the method's origin and its theoretical basis, elaborating the specific implementation steps, and analyzing in depth the research object and research theme. Furthermore, this paper proposes key areas for future research, aiming to bridge the gap between theoretical conceptualization and practical applications, and to offer a new research perspective and framework for the fields of human information behavior and user experience design. Related Articles | Metrics | Comments（0）

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A Review of the Behavioral Research on Conversational Search: Defining the Paradigm, Constructing Models, and Characterizing Behaviors Meng Gaohui　Liu Chang Journal of Information Resources Management    2025, 15 (4): 24-41.   DOI: 10.13365/j.jirm.2025.04.024 Abstract （547）      PDF（pc） （1862KB）（572）       Knowledge map    Save At the developmental turning point brought by the generative artificial intelligence (GenAI) wave, this paper provides a comprehensive review of research on conversational search behavior. It examines how the new paradigm transforms traditional perceptions of search behavior, summarizes the current state and limitations of this field, and offers valuable research directions for future studies. By reviewing the research progress in defining the overall characteristics of human-computer interaction, modeling the behavior categories and development processes of users and agents, and characterizing the behavior features and related factors of users or agents in conversational search, it argues that the main limitations of previous studies are that research objects seldom cover the cognitive and emotional activities that drive objective dialogue actions, research scenarios are mostly limited to simulated human-human dialogue scenarios, and research topics rarely involve the evaluation of user behavior performance and the enhancement of user capabilities. Future research should inherit and develop the cognitive research paradigm in the field of interactive information retrieval, expand the research scenarios to real human-computer dialogues under the GenAI scenario, and focus on evaluating and discovering better user behavior patterns. Related Articles | Metrics | Comments（0）