Abstract: [Purpose/Significance] In order to promote the standardization and digital transformation of Hainan sea fishing industry, this paper integrates knowledge management theory and Internet of Things technology to build intelligent management solutions and provide scientific and technological support for the upgrading of recreational fisheries. [Method/Process] Based on the real-time data acquisition and big data analysis technology of HiTo smart bracelet, the "Deshun Haitu" integrated management information service platform was designed and developed. The platform incorporated functional modules such as safety early-warning, resource scheduling, and user behavior analysis. Its efficacy was validated and refined through multiple iterations of case studies, expert evaluations, and simulation tests. [Result/Conclusion] "Desheng Haitu" integrated management information service platform based on HiTo smart bracelet can significantly reduce the rate of sea fishing accidents (down 35%), improve the efficiency of fishery resource allocation (28%), and enhance user activity (up 40%). Through the real-time perception and dynamic analysis of intelligent devices, accurate risk early warning and intelligent resource allocation can be realized, and a replicable technical path and management paradigm can be provided for the digital transformation of recreational fisheries.

Abstract: [Purpose/Significance] This study proposes a methodology and process for knowledge discovery in technology fields based on the integration perspective. By constructing a knowledge map of multi-energy technology and focusing on analyzing the integration features (e.g., synergistic energy utilization and system integration), this study aims to provide a new methodological tool for identifying the potential of technology integration. [Method/Process] By integrating different patent technology classification systems, this study innovatively constructed a multi-energy integration patent knowledge graph. It established a domain knowledge organization framework based on multi-technology classification fusion. The conceptual model was constructed by combining the "top-down" and "bottom-up" methods, with the low-carbon energy technology field using as the empirical research object to systematically analyze the multi-energy fusion trend, fusion signal, and multi-energy fusion potential of low-carbon energy. [Result/Conclusion] Empirical study shows that combination of knowledge map, and bibliometrics can help analyze the development trends of low-carbon energy convergence, reveal the characteristics of technology integration of multiple low-carbon energy sources, and focus on specific domains to explore the potential and technological evolution path, to provide a decision-making basis for the development and application of low-carbon multi-energy integration technology.

Abstract: [Purpose/Significance] By facilitating the externalization of tacit knowledge, this study aims to drive knowledge innovation within virtual brand communities, ultimately injecting strong momentum into corporate innovation. [Method/Process] Using Xiaomi community members as research subjects, this study conducted coding analysis and relationship mapping of interview data. Grounded in the Stimulus-Organism-Response (SOR) theory, a model was developed to identify the influencing factors and pathways of tacit knowledge externalization among virtual brand community members. Finally, promotion strategies were proposed from three dimensions: individual, community, and brand dimensions. [Result/Conclusion] Community members' risk perception and benefit considerations are direct factors influencing tacit knowledge externalization behavior. Members' self-efficacy and intrinsic motivation, along with community-level factors (including member participation, content dissemination mechanisms, management, and ecosystem), as well as members' emotional identification with the brand and continuous attention to product innovation, indirectly affect tacit knowledge externalization by influencing members' risk perception and benefit considerations.

Abstract: [Purpose/Significance] By constructing a model of online application behavior among fine arts undergraduates, this study aims to provide a basis for art universities to understand and grasp students' online behaviors, thereby monitoring their digital activities and exploring innovative online ideological and political education models in higher education. [Method/Process] Based on grounded theory and using the qualitative data analysis tool NVivo 12, interview texts were subjected to open coding, axial coding, selective coding, and theoretical saturation testing to develop a model of online application behavior for fine arts undergraduates. [Result/Conclusion] The model reveals that under different online and real-world contexts, influenced by personal traits and realistic constraints, fine arts undergraduates' online behaviors exhibit similar group characteristics while differing in behavioral purposes and patterns. The model summarizes six core categories (representation layer, environment layer, goal layer, behavior layer, extension layer, and constraint layer), as well as 18 main categories. Based on these core categories, the study further proposes that art universities should enhance the effectiveness of online ideological and political education by focusing on three aspects: environmental governance, goal guidance, and behavior correction, thereby providing a foundation for properly guiding students' online behaviors.

Abstract: [Purpose/Significance] Many scholars are using qualitative comparative analysis and structural equation modeling to conduct empirical analysis in the field of library and information, but few relevant studies are comparing the two methods. This study can provide a useful reference for selecting appropriate methods to explore the problems in the field of library and information, which is of great benefit to improving the overall research level of this discipline. [Method/Process] The principle, operation procedure, and application of QCA and SEM are elaborated and compared, and then QCA and SEM are respectively used to conduct an empirical study on the willingness of online knowledge paying users to continue using. [Result/Conclusion] The results showed that there were differences between the two methods. In terms of theoretical basis, QCA theory is based on set theory and Boolean algebra, while SEM theory is based on analysis of variance. In terms of causal analysis, QCA emphasizes equivalence and asymmetry, which is suitable for analyzing complex and interrelated problems with multiple antecedents, and SEM emphasizes linearity and symmetry, which is suitable for analyzing the relationship between two variables. In terms of research objectives, QCA is mainly to construct new theories and extend existing theories, while SEM is mainly to verify and improve existing theories. In terms of logic analysis, QCA is mostly an exploratory analysis method in logic analysis, while SEM is mostly a verification analysis method. In empirical studies, the multiple pathways resulting from QCA can complement the univariate conclusions of SEM.

Abstract: [Purpose/Significance] Addressing issues such as single point of failure, privacy leakage, and insufficient ability of traditional digital resource preservation methods, an integrated model based on blockchain and distributed storage is proposed to solve the core challenges such as easy data tampering, inefficient permission management and a lack of trust in cross-institutional collaboration. [Method/Process] This study designed a hierarchical architecture model that integrates blockchain depositary metadata and IPFS chunked storage files. And smart contracts were utilized to automate processes including resource upload, permission control and data recovery. Data privacy was safeguarded through AES encryption. The model's reliability was rigorously verified based on a hash collision probability calculation (4.26×10^-27) and a quantified disaster tolerance capacity quantification (annual file recoverability rate of 99.99%). [Result/Conclusion] The model significantly outperforms other methods in data immutability, privacy protection (it takes 3.68×10⁵¹ years to crack AES-256) and disaster tolerance capacity. And it is suitable for high-security scenarios such as digital archives and medical data management. The study also proposes strategies such as hierarchical storage, data deduplication and compression to optimize system performance and reduce cost. A modular design reduces development complexity, while the integration of managed services enhances deployment efficiency. This research shows that the collaborative mechanism of blockchain and IPFS provides a reliable path for digital resources preservation. In the future, it is necessary to further balance performance and cost to support large-scale applications.

Abstract: [Purpose/Significance] To identify key technological areas for green development, predict technology evolution trends, and provide a scientific basis for technological innovation, policy formulation, and sustainable development. [Method/Process] Data from the patsnap patent database was used as the sample source. Techniques such as TF-IDF, LDA topic modeling, and perplexity were applied to explore the distribution of topic terms and extract key themes. Additionally, semantic network topic clustering was conducted to achieve technological association analysis, comprehensively analyzing the current status and trends within the patent data. [Results/Conclusion] The research reveals that green development technology is in the early stages of maturity. Patent topics can be classified into seven categories: green production technology, green building construction technology, motor drive technology, etc. The development direction involves a comprehensive transformation from single technologies to system integration, from resource-efficient utilization to circular economy, from traditional energy to renewable energy, and from single environmental governance to integrated ecological management. By analyzing the current status of green development technology from a systematic perspective and exploring its development trends, this article provides valuable insights for the advancement of related technologies in this field.

Abstract: [Purpose/Significance] To explore the characteristics and inherent rules of health information interaction behavior among young social media users, and provide measures and solutions for social media intervention in users' positive health behavior. [Method/Process] In this paper, by collecting interview data, log files, experimental video data and Xiaohongshu note data, and adopting the data analysis methods of grounded theory and text mining, an in-depth analysis was conducted on the characteristics of young social media users' health information acquisition behaviors, the logic of health information quality evaluation, and the patterns of health information retrieval behaviors. And based on Engeström's Activity Theory and Kuhlthau's Information Search Process Model, an activity model of the health information retrieval behavior patterns of young social media users was constructed. [Result/Conclusion] The following conclusions were drawn: The sources from which young social media users obtain health information exhibit the characteristics of diversified choices that are mainstream-oriented and demand-driven. The ways in which they pay attention to health information content are mostly demand-based retrievals triggered by recommendations, and the categories of attention fall into multiple core areas of concern. Young social media users' evaluation paths for health information quality follow a dual path of subjective cognition and objective perception. The basis for judging the trustworthiness of health information is a collaborative inspection-style information assessment through the convergence of content and the consensus of comments, and the evaluation method of health information is based on the principle of the minority obeying the majority.

Abstract: [Purpose/Significance] Technology forecasting is a field of research related to future technology development trends and technological innovation. This paper aims to identify the current research hotspots and frontiers in the field of technology forecasting, to provide guidance for the technological innovation of enterprises and organizations, helping them seize opportunities and avoid risks. [Method/Process] Technology forecasting literature from WoS and CNKI (2001—2024) was analyzed using VOSviewer and CiteSpace to identify literature characteristics, hotspots, and frontiers. [Result/Conclusion] The result shows that: ①The volume of articles published in the field of technology forecasting has grown steadily at domestic and international, and the core journals are distributed in the fields of information science, management and other disciplines. ②A stable core authors group has formed in the field of technology forecasting at home and abroad. In China, collaboration remains predominantly intra-institutional, and there are cross-institutional, with cross-institutional ties often stemming from mentor-apprentice relationships. Internationally, cross-institutional collaboration is more prevalent, frequently facilitated by jointly-trained scholars and visiting academics who serve as bridges for research partnerships. Notably, Chinese scholars have emerged as key contributors to international technology forecasting research. ③Regarding research hotspots, domestic research focuses on the research of emerging and disruptive technologies, technology opportunities, and technology forecasting methods. Foreign countries focus on technology development trend research, emerging technology assessment and forecasting research, technology convergence and technology intelligence research, technology opportunity discovery and analysis research. ④In terms of research frontiers, identification and prediction of disruptive and emerging technologies, research on technology convergence and technological innovation, and optimization of technology opportunity identification and discovery methods are the research frontiers in the field of domestic technology forecasting. The research frontiers in the field of foreign technology forecasting mainly focus on the improvement of technology forecasting methods and the discovery and analysis of technology opportunities.

Abstract: [Purpose/Significance] Currently, universities are facing both opportunities and challenges brought by artificial intelligence (AI), as well as dual pressures in the construction of "Double First Class" universities. Achieving the assistance of AI in cultivating high-quality talents and building high-quality disciplines is of great significance. [Method/Process] From the perspective of (soft) knowledgeization and knowledge services, this paper took a problem-oriented approach to analyze artificial intelligence and “soft knowledgeization” of higher education., and reveal its essential symbiotic relationship with AI, based on the real challenges faced by universities, the priority of talent cultivation, the distinctive characteristics of soft knowledge that influence students and faculty, and the competitive dynamics among administrators, educators, and students. Based on the cultivation of soft knowledge talents as the inevitable choice and breakthrough for universities to alleviate dual pressures, the study analyzed the mission of soft knowledge talents cultivation and proposed a knowledge service system to support this educational approach. [Result/Conclusion] By implementing customized educational strategies grounded in knowledge services, fostering open collaboration, and integrating liberal arts and sciences, universities—particularly undergraduate institutions—can improve the quality of talent training. This approach aims to develop unique, competitive individuals equipped with strong soft knowledge and nurture high-end innovative talents with a robust foundation in both liberal arts and sciences. Ultimately, this strategy promotes sustainable development amid dual pressures competition, contributing to the cultivation of talents essential for high-level security and quality development in the era of artificial intelligence.

Abstract: [Purpose/Significance] Exploring the impact of perceived personality matching between users and chatbots in the dimensions of agency and communion on intimacy in the context of social support, providing theoretical basis and practical guidance for improving the service quality and user experience of social support chatbots. [Method/Process] Based on the user perception perspective and social exchange theory, scenario experiments were conducted to obtain personality and user experience data. Polynomial regression and response surface analysis methods were used to explore the impact mechanism of matching agency personality and perceived competence, communion personality and perceived warmth on user intimacy. [Result/Conclusion] There are significant differences in the impact of different combinations of user personality and chatbot perceived personality on users' self-disclosure willingness under different matching types in various dimensions; User’s perceived competence and warmth of chatbots are key factors affecting their self-disclosure; Users’ self-disclosure plays a mediating role in the relationship between perceived personality matching and intimacy. This study reveals the essence of the impact of personality matching on the user experience of human-AI interaction, confirms the important role of self-disclosure in the establishment and development of human-AI relationships, and provides guidance and suggestions for the design of social support chatbots.

Abstract: [Purpose/Significance] In order to understand the implementation status of scientific research achievements evaluation in Chinese universities under the guidance of "Breaking the Five-Only Criteria", grasp the reform direction of scientific research evaluation, and promote the healthy development of academic ecology in universities. [Method/Process] This paper uses the content analysis method based on policy text coding to analyze 95 university research reward policy texts, systematically sort out the evaluation indicators and criteria of different types of scientific research achievements, and reveal the reform ideas of university research achievement evaluation. [Result/Conclusion] It is found that the scientific research achievements of universities include five types: award achievements, academic papers, academic works, technology property rights, think tank consulting results, etc. The overall scientific research reward system has problems such as unbalanced attention, inadequate classification of disciplines, and imperfect qualitative evaluation system. At the institutional level, it is necessary to improve the relevant provisions of non-theoretical results evaluation, expert review, subject classification evaluation, and human-machine collaborative evaluation, and guide scholars to return to the essence of scientific research.

Abstract: [Purpose/Significance] Investigating the characteristics of AI-generated academic journal content and establishing a multidimensional analytical framework are crucial for identifying improper use of AIGC in manuscripts, addressing challenges in peer review complexity, and upholding the quality and credibility of academic publishing. [Method/Process] This study analyzed journal articles with varying AIGC values across eight dimensions: citations, data, viewpoints and conclusions, structural framework, logical coherence, content consistency, conceptual clarity, and linguistic expression. Both explicit and implicit features of AI-generated content were systematically extracted. The practical efficacy of this approach in peer review was validated through cross-verification between AIGC-CHECK system outputs and empirically observed characteristics of AI-generated texts. A tri-level strategy was subsequently formulated, encompassing rapid preliminary screening, in-depth verification, and comprehensive countermeasures. [Result/Conclusion] Compared to relying solely on detection systems or reviewers' experience, this approach offers a more effective method to address inappropriate AIGC usage, overcomes the limitations of single review techniques, and provides practical value in enhancing review efficiency and publication quality.

Abstract: [Purpose/Significance] This article focuses on the privacy leakage risks of elderly people in online shopping, aiming to raise their awareness of privacy protection, help them better adapt to the era of online shopping, and ensure personal information security. [Method/Process] This article took the use of shopping apps by elderly people as the research object, aiming to explore the factors that affected privacy disclosure willingness. A structural equation model was established based on privacy calculation and trust theory. Data was collected through a questionnaire survey, and SPSS 26.0 and Amos 24.0 software were used for data analysis to verify whether the hypothesis path coefficient was valid. [Result/Conclusion] Personalized recommendations, price differences, platform trust, and after-sales service trust all affect the elderly's willingness to disclose privacy in online shopping. Perceived benefits and perceived risks are key factors determining whether elderly people are willing to disclose personal privacy in shopping apps.

Abstract: [Purpose/Significance] Fact-checking is an effective strategy to combat the dissemination of misinformation. Exploring the mechanism of how fact-checking types (crowdsourced and AI fact-checking) influence users' information participation behavior can help social platforms improve and optimize their measures for misinformation governance. [Method/Process] Based on real data from social media platforms, this study used analysis of variance to investigate the impact of fact-checking on users' information participation behavior, while considering the moderating effect of source credibility. [Result/Conclusion] The empirical results show that crowdsourced fact-checking significantly affects users' information engagement behavior, with positive fact-checking promoting information participation behavior and negative fact-checking inhibiting it. AI fact-checking positively influences users' information engagement behavior, and the combination of AI and crowdsourced fact-checking also positively affects users' information engagement behavior. Source credibility positively moderates the relationship between crowdsourced fact-checking and information engagement behavior, as well as the relationship between AI fact-checking and information engagement behavior. This study reveals the impact of different types of fact-checking and their integration on information engagement behavior, providing theoretical support for social media platforms to fully utilize collective intelligence and AI for fact-checking and misinformation governance.

Abstract: [Purpose/Significance] This study aims to measure the influence of scholars objectively and scientifically, identify a group of scholars with rich scientific research achievements and outstanding academic influence in China in the past 10 years, and guide Chinese scholars to publish more outstanding achievements in domestic journals. [Method/Process] The selection and evaluation process primarily employed bibliometric methods. For assessing individual paper impact, we utilized the Paper Citation Standardized Index (PCSI) as the evaluation metric. Author contribution weights were allocated using an optimized harmonic allocation method. The final selection of highly cited scholars was based on calculating the 'Total Author PCSI' derived from each researcher's complete publication record. [Result/Conclusion] Approximately 30,000 individuals were selected as "Top 1% Highly Cited Scholars", and around 89,000 individuals were selected as "Top 5% Highly Cited Scholars". This research achievement has achieved a comprehensive quantitative evaluation of Chinese scholars for the first time, providing a new perspective for the academic community to identify high-end talent teams, which is conducive to stimulating scholars' continuous innovation and encouraging the return of excellent domestic scientific research achievements. The selection results show that in terms of disciplinary distribution, applied economics, education, business administration, public management, and agricultural and forestry economic management have the highest number of highly cited scholars selected in the fields of humanities and social sciences. In the field of technology, disciplines such as clinical medicine, traditional Chinese medicine, electrical engineering, nursing, and civil engineering have the highest number of highly cited scholars selected. In terms of regional distribution, the regions with the highest number of highly cited scholars are Beijing, Jiangsu, Shanghai, Guangdong, and Hubei, which are developed in education and scientific research. In terms of institutional distribution, Tsinghua University, Peking University, Wuhan University, Renmin University of China and Beijing Normal University are the five institutions with the largest number of selected scholars.

Abstract: [Purpose/Significance] This paper aims to comprehensively grasp the theoretical and practical frontiers of data governance in the field of library and information science, construct a systematic cognitive framework, and provide a strong reference for relevant policy formulation, institutional design, and strategic planning implementation. [Method/Process] With the help of CiteSpace and VOSviewer visualization tools, the data source of this paper was CNKI. Through the analysis of the topic information, this paper built the research framework of the field, extracted the frontier hotspots of the field, and explored the development and evolution of the field. [Result/Conclusion] The research literature on data governance in the field of Library and Information Science in China shows an exponential growth trend and can be divided into two stages (2015-2019 and 2020 to now). Through topic clustering, five topics are summarized, including governance theory system, governance technology system, governance business model, governance practice plan, governance policies and laws, and regulations. Further prospects for the research on data governance in China are put forward, which provide theoretical and practical reference for better playing the role of "data element ×" and promoting the modernization of the national governance system.

Abstract: [Purpose/Significance] Developing a scientific tool for measuring job burnout can help to accurately assess the job burnout status of archive workers in the whole society or specific fields, identify the influencing factors of job burnout generation and development, and optimize and adjust them in a targeted manner. [Method/Process] Based on existing research literature, a measurement scale for job burnout of archivists has been constructed. The optimized and revised scale consisted of 4 dimensions and 21 questions, with good reliability and validity, and could be used as a measurement tool for job burnout of archivists. [Result/Conclusion] Based on this measurement of archivists, the results showed that 144 out of 291 archivists surveyed exhibited occupational burnout, accounting for 49.48%. The study found that the main influencing factors of occupational burnout among archivists include social identity, attitudes, and professional treatment of colleagues and service users, work area, professional background, and health status. Suggestions should be made to alleviate the occupational burnout of archivists by cultivating their identification with archival work, enhancing their information literacy, and strengthening the promotion of archival work.

Abstract: [Purpose/Significance] In view of the current situation of diversified channels and increasingly expanding scope of knowledge diffusion in academic papers in the new media era, exploring the methods for evaluating the effect of knowledge diffusion in academic papers and its influencing factors is conducive to promoting the effective diffusion of knowledge in academic papers and improving the communication effect. [Method/Process] Organic integration of data generated by formal and informal carriers, construction of a multi-dimensional, multi-level academic paper knowledge diffusion effect evaluation model, to evaluate the effect of knowledge diffusion of academic papers, and as a basis for this, and to explore the impact factors affecting the effect of knowledge diffusion of academic papers, and based on this, put forward to promote the effect of the diffusion of knowledge of academic papers strategies, and take the highly cited papers in the field of biochips as an example for empirical research. [Result/Conclusion] The formula for measuring the knowledge diffusion effect of academic papers can to some extent select academic papers with good knowledge diffusion effect; twelve factors influencing the effect of knowledge diffusion of academic papers are explored and it is found that there are two significant influences of formal carriers(the amount of references and the time of first citation), seven significant influences of informal carriers(such as the time of publication and the h index of the first author), six significant influences of knowledge diffusion of academic papers(such as the time of publication and the number of interdisciplinary disciplines); and proposes four strategies to enhance the effectiveness of knowledge diffusion in academic papers.