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] The objective is to gain a comprehensive and in-depth understanding of the research dynamics and development trends in the field of digital academic services in Chinese libraries, ultimately providing a reference for enhancing the value and contribution of libraries in the academic research ecosystem. [Method/Process] Using the literature survey method to map and analyze the research on digital academic services of Chinese libraries and the scientific research life cycle from 2021 to 2025, the main research content is summarized from two major dimensions: the design of the digital academic service system and the practical approaches. Building on this foundation, and incorporating the new demands generated under the fifth research paradigm and a new stage of development for smart libraries, the future development direction and key areas of focus for digital academic services in libraries were further explored. [Result/Conclusion] The design of the digital academic service system for libraries primarily encompasses two aspects: service framework and service strategy. In terms of practical paths, a comprehensive collection of digital academic services has been established, centered around consulting decision support services, scientific research data services, AI intelligent assistance services, academic publishing services, digital humanities services, and various personalized services tailored by libraries based on specific needs. Given the characteristics of data-intensive, open science, and intelligent technology-assisted scientific research, libraries should prioritize industry trend prediction and research, implement the "theory-practice-new theory" cycle service, reconstruct the library's core capabilities and intelligent service system, precisely plan service projects closely related to users, and promote user experience optimization and continuous innovation in library services.

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 study aims to analyze the potential risks of using AIGC tools during academic research, study the strategies to avoid these risks and provide references and guidance for researchers so that they can use AIGC tools in compliance with rules and laws. [Method/Process] This study sorted out the policies and regulations related to the application of AIGC in academic fields at home and abroad, summarized and analyzed the main risks of using AIGC. Then, combined with the researchers’ academic research process, risk avoidance strategies and feasible suggestions for using AIGC at different stages were proposed. [Result/Conclusion] The risks of using AIGC tools for researchers mainly focus on the security of input content, the reliability of output results, academic ethical risks, and potential legal risks. Researchers should enhance their risk-awareness, understand the policy regulations, know the usage boundaries for different research stages and scenarios very well, and regulate their usage behavior to ensure that AIGC tools play a positive role in academic research.

Abstract: [Purpose/Significance] Aiming at personal knowledge management, this paper provides a personal knowledge management tool with moderate learning difficulty, complete functions, safety, and reliability, in order to improve the level of personal or team knowledge management. [Method/Process] Firstly, a personal knowledge practice framework was constructed, and the four basic processes of personal knowledge management, namely, acquiring knowledge, organizing knowledge, absorbing knowledge, and applying knowledge, as well as the main functional requirements that an ideal personal knowledge management tool should meet were proposed. Then, the main requirements of using Zotero in the stages of acquiring knowledge, organizing knowledge, absorbing knowledge, and applying knowledge are introduced, including acquiring Web page information and building a knowledge network system. The use of auxiliary translation technology and AI technology in Zotero is introduced. Finally, the issues that should be paid attention to when using Zotero were summarized, that is, the need to comply with confidentiality requirements, pay attention to the integrity of metadata, and review and organize regularly. [Result/Conclusion] Zotero meets the needs of the entire process of personal knowledge management, can greatly improve the efficiency of knowledge management, is suitable as a personal knowledge management tool, and should be actively promoted and applied.

Abstract: [Purpose/Significance] By analyzing the application scenarios of virtual digital human technology, we aim to further explore its innovative potential in science popularization and teaching, in order to provide new solutions for digital education and knowledge popularization.[Method/Process] Systematically review virtual digital humans’ technical principles and key technologies, use case analysis to explore their cutting-edge applications and practical research in segmented fields, and empirically demonstrate the potential of virtual digital humans in science popularization and teaching. [Result/Conclusion] Virtual digital humans, as a new medium, can lead the innovative expression of popular science content and achieve a more immersive and participatory teaching experience with their high degree of anthropomorphism and interactivity. The current challenges come from graphics and animation technology, deep learning technology for speech features, interactive and intelligent technology, cognitive modeling and learning algorithms, LLM technology for large language models, and the core technologies behind computing power.

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] 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] The research on the users’ purchasing behavior of live broadcast E-commerce is of great significance for the development of live broadcast E-commerce, which is conducive to the targeted adjustment and improvement of live broadcast strategy. [Method/process] This paper studies the influencing factors of users' purchasing behavior of live broadcast E-commerce, constructs an index system from four aspects of anchor ability, commodity information, user attribute, and comprehensive ability of live broadcast team, and draws a conclusion with an example. Through the release of questionnaires and expert consultation to collect data, this paper uses fuzzy comprehensive evaluation method for the first evaluation of all levels of indicators, then uses analytic hierarchy process for pairwise comparison, builds a matrix, gets the final weight, and accurately analyzes the influencing factors of users’ purchasing behavior. [Result/conclusion] Credibility of commodity information and comprehensiveness of commodity display are the first major factors of affecting users’ purchasing behavior. Under segmentation, the most important factors are commodity quality, information detail level and online reputation, follow by the professional ability of the anchor. There are great differences between users of different ages which influenced by anchors with different social identities, and real-time comment interaction is easier to promote user consumption. The continuous penetration of online shopping in the public makes the audience of middle and old users watching live broadcast E-commerce expand gradually, and has a strong development potential.

Abstract: [Purpose/Significance] This paper explores the application value of Artificial Intelligence Generated Content (AIGC) in public libraries, focusing on the group of minors. It proposes the innovative development path of AIGC-enabled minor services in public libraries, aiming to improve public libraries’ intelligence level. [Method/Process] By analyzing the concept of AIGC and the current research status of AIGC-enabled public library services for minors, we explored the empowering role of AIGC for public library services for minors and proposed the future development path of AIGC in library services for minors. [Result/Conclusion] AIGC strongly promotes the way, content, and effect of minors' services in public libraries towards diversification, personalization, efficiency and intelligence. In the future, public libraries need to make good use of the important value of AIGC technology by focusing on promoting intelligent search and consultation, enhancing the effectiveness of reading promotion, introducing virtual digital people, and creating a “second classroom” of literacy education. This will ensure the comprehensive development of minors and promote the intelligent transformation of public libraries.

Abstract: [Purpose/Significance] By analyzing the application scenarios and challenges of large models in the field of knowledge management, this paper aims to provide reference and inspiration for research and practice in related fields, promote the deeper application of large models in the field of knowledge management, and improve the user experience of knowledge management tools. [Method/Process] By tracking the dynamics of software and hardware vendors, commercial products, open source projects, academic research, and actual customer experience, the practical application of large models in the field of knowledge management, and the problems and challenges faced in the process were summarized and sorted out. [Result/Conclusion] Large models have become a powerful tool for knowledge management and have more and more practical applications, including assisting in document writing, automatically generating document summaries, using natural language to retrieve information, intelligent question answering, etc. These applications have changed the way traditional knowledge management operates, making it more efficient, intelligent, and user-friendly. However, the application of large models in the field of knowledge management also faces some unresolved problems, such as data privacy protection, intellectual property rights protection, knowledge pollution, high costs, and unstable content output, which have yet to be solved.

Abstract: [Purpose/Significance] This paper analyzes the scientific data policy texts released at the national level in China and describes the characteristics of national policy deployment, intending to better grasp the development trend of scientific data policy and providing important references for the formulation of scientific data related policies in China. [Method/Process] Based on the three-dimensional analysis framework of "policy tool - policy subject - data lifecycle" (i.e., X dimension, Y dimension, and Z dimension), the content analysis method and policy text measurement method were used to deconstruct and quantify 106 scientific data policies published at the national level from 2005 to 2022 in China. [Result/Conclusion] The distribution pattern of "authority policy tools + capacity policy building tools" is formed. The State Council, the Ministry of Science and Technology, and the People's Congress, as the main subjects of scientific data policy, are making unified planning and management of scientific data. The scientific data policy aims to promote the use and sharing of data while increasing investment in basic capacity building for scientific data development. Notably, the absence of incentive tools, symbols, and exhortation tools is serious, and the internal structure of policy tools is not balanced. The State Council, the Ministry of Science and Technology, and the People's Congress bear a heavy burden in scientific data management. The current policy has less deployment for the data acquisition and data processing stage. Proposals are given to increase the proportion of incentive tools and symbolic and exhorting tools, optimize the internal structure of various types of policy tools, effectively streamline administration and delegate power, rationally adjust the pressure of policy subjects, and strengthen the management of the whole lifecycle of scientific data.

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] 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] 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] This study is to combine information cocoon, echo chamber and filter bubble, and focuses on the differences and connections between their respective research areas. [Method/Process] Advances in technology were quietly changing the pattern of user information behavior, and the problem of information narrowing brought about by information cocoons, echo chambers and filter bubble effects was gradually drawing the attention of scholars. Using a visual bibliometric research method, this study extensively collected relevant domestic and international research literature from 2006-2021, and combed through the research lineage of information cocoon, echo chamber and filter bubble with a comparative analysis, and set up group polarization as a secondary research object to supplement. [Result/Conclusion]The results of the study found that: ①domestic and international scholars generally agreed that information cocoon, echo chamber and filter bubble all led to group polarization, among which information cocoon was the most obvious; ②in terms of the number of publications, domestic and foreign research could be divided into four research themes, and there was a clear difference between the two in specific areas; ③domestic studies mostly focused on the definition of the concept and the analysis of the adverse consequences, and the research methods were mostly qualitative, while foreign studies focused on the mechanism of the above three, and the research methods were mostly quantitative; ④the future trend of related research at home and abroad was consistent, namely, the emotional dimension as an important research object to study the mechanism of the above three generation.

Abstract: [Purpose/Significance] Reviewing the current status of debunking research in China, analyzing research hotspots and trends, and providing references for related research in this field. [Method/Process] A visualization software, CiteSpace, was used to perform bibliometric analysis on CSSCI journal papers on CNKI from 2007 to 2023, and the author, institution, and keyword knowledge map were drawn to analyze the hot spots and frontier trends of rumor-refuting research. [Result/Conclusion] The research finds that the domestic rumor-refuting research shows a steady growth. The themes are focused on the intention and law of rumor-refuting information dissemination, the rumor-refuting effect and evaluation, the rumor-refuting mechanism and strategy. The changes in research hotspots go through the initial exploration stage of the rumor-refuting strategy, the in-depth practice stage of the rumor-refuting platform, and the steady improvement stage of the rumor-refuting effect. The research front trend is the fact-checking of artificial intelligence-generated content, the psychological mechanism of rumor-refuting effect and attitude change, and the rumor-refuting mechanism of man-machine collaboration.

Abstract: [Purpose/significance] Medicinal plants are one of the core resources of Chinese medicine, and strengthening the organization and electronic utilization of medicinal plant information is of great significance to the inheritance and development of Chinese medicine. [Method/process] In this paper, the pattern layer of the knowledge graph of medicinal plants was constructed, and then 265 medicinal plants were screened out by comparing multiple databases such as Chinese Pharmacopoeia, TCMID, PPBC and CTD, a nd multi-source heterogeneous data were integrated, and Neo4j was used to construct a multimodal knowledge graph of medicinal plants. On this basis, AC automaton was used to recognize the user's question entity and TextCNN was used to complete the question intent recognition, so as to realize the text-based intelligent answer function. By comparing six image recognition models such as VGG, ResNet, DenseNet, MobileNet, and EfficientNet, the EfficientNet-B3 model is preferred to realize the image-based intelligent question and answer function, and introduced data enhancement and label smoothing methods to improve the image recognition efficiency, and finally used the Python language PyQt library to realize the medicinal plant question answering system. [Result/Conclusion] A multimodal knowledge graph including medicinal plants and various botanical formulas, medicinal materials, compounds and images is constructed, including 340 772 entities and 2 530 067 relationships. Based on this, an intelligent question answering system for medicinal plants is constructed, which can feedback the query results according to the user's natural language questions and picture questions, and the experimental results show that the image recognition accuracy of the system reaches 83.53%.

Abstract: [Purpose/Significance] The study provides valuable references for understanding and predicting older adults’ smart senior technology continuance intention, which can help guide the design and improvement of smart senior technologies and further enhance the user experience. [Method/Process] The meta-analysis method was used to comprehensively analyze 34 quantitative research papers, focusing on the relationship between 14 groups of key variables that affect the intention of the elderly to continue to use smart senior technology, and the source of heterogeneity of the research results was analyzed with the help of the moderating effect test. [Result/Conclusion] The findings showed that social influence, facilitating condition, satisfaction, perceived usefulness, perceived ease of use, trust, and participation were significantly and positively related to smart senior technology continuance intention. In contrast, perceived risk and technology anxiety were negatively associated with smart senior technology continuance intention. In addition, the gender composition of the sample, the level of economic development of the country, the type of technology, and the size of the sample can moderate the correlations between the variables, resulting in differences between the findings.

Abstract: [Purpose/Significance] This study systematically investigates the impact of government microblog collaboration on public participation behavior in natural disaster crisis situations, in order to help the government respond to sudden crisis events more effectively and collaboratively, and promote the active participation of the public. [Method/Process] This study takes the “Beijing-Tianjin-Hebei Rainstorm” in 2023 as an example, and analyzes 625 blog posts and 9426 user comments from 5 typical national government microblogs, and establishes a theoretical analysis framework of collaborative functions, collaborative departments, and collaborative levels in the light of the theory of holistic governance. At the same time, we combine the public participation ladder model to explore the public participation behavior and the level of participation. Qualitative content coding, machine learning, statistical analysis, and other methods are comprehensively applied to reveal the collaborative features of government microblogs and the correlation with public participation behavior. [Result/Conclusion] The results of empirical analysis show that the collaboration of government microblogs is mainly among governmental organizations at the same level and with the news media, and the collaborative functions are information synergy, call for action and emotional connection, and the collaborative features have the characteristics of time stage. Emotional interaction is the most prominent behavior in public participation. When government microblogs synergize with a clear call to action, they are more likely to inspire higher levels of public participation.