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] 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] Crowdsourced fact checking has been proposed by various social media platforms as a measure for misinformation governance. Exploring the relationship between crowdsourced fact-checking and users' information engagement behavior is conducive to improving platforms and optimizing governance measures. [Method/Process] This study used the intergroup experimental design: 2(descriptive social norms: existence Vs. non-existence) × 2(source credibility: high Vs. low), 2(positive check: existence Vs. non-existence) × 2 (source credibility: high Vs. low), 2(negative check: existence Vs. non-existence) × 2 (source credibility: high Vs. low) to explore the influence mechanism of user information engagement behavior in terms of descriptive social norms, positive and negative check, and source credibility. [Results/Conclusions] The empirical results show that descriptive social norms (DSNs) positively influence user information engagement behavior, and descriptive social norms (DSNs) and user information engagement behavior have an inverted U-shaped relationship. Source credibility positively moderates the relationship between descriptive social norms (DSNs) and user information engagement behavior. Source credibility has a positive moderating effect on the relationship between positive checks and user information engagement behavior; the higher the source credibility, the greater the impact of positive checks on user information engagement behavior. Source credibility has a negative moderating effect on the relationship between negative checks and user information engagement behavior; the higher the source credibility, the smaller the impact of negative checks on user information engagement behavior.

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] Currently, the paradigm of data-intensive scientific discovery in scientific research is evolving towards intelligence. AI-driven scientific research (AI4Science) is becoming the engine of technological innovation and a new paradigm for scientific research. This study will delve into the experimental schemes within AI4Science, revealing the application of AI technology in research methods, tools, and means through the analysis of experimental schemes in scientific literature, providing new research perspectives for scientific researchers. [Method/Process] ① Knowledge extraction and modeling of the experimental scheme. Ontology modeling technology was used to realize the unified knowledge modeling of experimental methods and experimental principles in different subject areas. The domain knowledge graph of organic solar cells was constructed on the basis of ontology modeling. ② Research on intelligent recommendation of the experimental scheme based on the knowledge graph. The relationship between entities was mined in the domain knowledge graph to realize the intelligent recommendation of the experimental scheme. [Result/Conclusion] On the basis of Graph2vec representation technology and GPT embedding representation, GraphGPT Net is proposed as a new algorithm for knowledge graph semantic integration of the experimental scheme. The best performance is achieved on Recall@20 with a score of 0.0299, which proves its remarkable ability to recommend experimental schemes.

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.

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] 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] 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] 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] 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 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] 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] 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 recent years, the concept of open science has been widely recognized and highly valued by governments. Many foreign universities and research institutions have incorporated open science into their scientific research management systems, and have carried out a large number of open scientific research work, which has achieved significant economic benefits. [Method/Process] This paper systematically reviews the cost estimation research of open science at home and abroad, and summarizes that the cost estimation research of open science mainly includes three aspects: scientific research funding institutions, scientific researchers and scientific research projects based on the open scientific research system, and systematically analyzes the measurement objects, calculation methods, quantitative benefits, monitoring and evaluation, etc. [Result/Conclusion] At present, scholars pay more attention to comprehensively evaluating the impact of open access/science on traditional scientific research funding, economic cost, knowledge diffusion, and discipline development, but there are also some shortcomings. In the future, research on the innovation of open science cost estimation, in-depth analysis of the impact of policy implementation, and comparative research on the practice of open science in different disciplines can be carried out.

Abstract: [Purpose/Significance] By comparing and analyzing the abstracts of Chinese papers generated by typical Large Language Models at home and abroad, we summarize the similarities and differences between the two, and provide references for the subsequent in-depth development of the Large Language Models and the development of research. [Method/Process] 121 topics in the discipline of "Library, Intelligence and Documentation " in the annual project of the National Social Science Foundation of China in 2023 were selected as the topics. The Chinese abstracts were generated by ChatGPT4.0 and ERNIE 4.0 respectively, and were analyzed in terms of the characteristics of high-frequency words, the distribution of words, the number of sentences, and the length of the abstract content to explore the similarities and differences of the content generated by the Large Language Models at home and abroad through the data preprocessing and the text analysis. Then, the comparison was also made with the abstracts written in the Chinese journal “Library and Intelligence Service” to determine whether the abstracts generated by the large language model are in line with the norms of Chinese thesis writing.[Result/Conclusion] The abstracts generated by ERNIE Bot are shorter, with fewer words, and more suitable for Chinese paper writing standards, while GPT generates abstracts with more words and sentences on average. By comparing the gaps and characteristics of the contents generated by the two typical Large Language Models, we can provide certain references for the improvement and further in-depth development of the Large Language Models.

Abstract: [Purpose/Significance] Discovering research questions and methods from a vast corpus of scientific literature contributes to uncovering research trends, promoting innovation technical approaches, and exploring patterns of knowledge evolution and dissemination in scientific research. [Method/Process] This paper proposed an integrated model for the joint extraction of “Problem-Method” pairs in scientific literature, combining syntactic structural information and semantic relationships. The model employed an encoder-decoder architecture. At the encoding stage, we focused on the abstract text of scientific literature, extracting Subject-Action-Object (SAO) triplets to represent the relationship between research questions and research methods (i.e., research method - acts on - research question). We constructed a semantic association graph based on SAO triplets and utilized Graph Attention Neural Networks (GAT) for encoding. The resulting encoding, combined with the abstract text, serves as input features for the decoder. At the decoding stage, a pointer network was used to extract research questions based on previously extracted research methods, enabling the joint extraction of “Problem-Method” pairs. [Results/Conclusion] Experiments indicate that our model performs well in terms of evaluation metrics and human assessment, enhancing the ability to extract core research questions and methods from the scientific literature.

Abstract: [Purpose/Significance] Public digital cultural resource platforms possess unique advantages in cultural resource integration and service. They are crucial tools for public cultural institutions such as libraries, museums, and archives to activate their resource advantages and enhance service levels. Investigating and summarizing the advanced experiences of mature cases can provide recommendations for the construction of related projects in China. [Method/Process] This study selected domestic and international Public digital cultural resource platforms, investigated and analyzed their resource preservation and service methods, and focused on the advanced explorations of the Europeana project in resource organization models, technology, and digital cultural resource services. Then, it proposed relevant optimization paths suitable for local projects. [Result/Conclusion] The research finds that standardized linked data models, systematic resource integration networks, and open and diverse service models are key factors contributing to the success of the Europeana project. Local projects should draw on relevant experiences and continuously improve in standardizing data formats and updating service concepts.

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%.