[Purpose/Significance] This study aims to explore the dynamic changes and interactions among various elements in the data transaction market, reveal the impact mechanism of data transaction on the market and social economy, and explore more effective management and trading modes. [Method/Process] This study adopted the system dynamics method to explore the data circulation mechanisms and their dynamics in the data transaction market. The market was subdivided into four core subsystems: data asset management, transaction mechanism, supervision and compliance, and market dynamics. Scenario simulations were carried out by Vensim to explore the interactions between the subsystems and their impact on the overall performance of the market. [Result/Conclusion] Through the systematic analysis of the data transaction market, this study aims to reveal the key driving factors and core problems in the data circulation, propose strategies to promote the healthy development of the market, and provide references for relevant policy formulation and market practice.

[Purpose/Significance] The phenomenon of knowledge withholding among users in virtual academic communities is a critical issue that affects knowledge sharing, innovation, and community development. Drawing upon relevant theories from sociology and psychology, this study delineates the multiple factors influencing knowledge withholding in virtual academic communities from both individual and community environment perspectives. [Method/Process] A two-stage qualitative and quantitative mixed method based on csQCA and decision trees was proposed. User data from virtual academic communities in three different disciplines, science and engineering, management and economics, and medicine, were collected through questionnaire to compare and analyze the multiple configurations of knowledge withholding among users. [Result/Conclusion] The study reveals that: (1) Knowledge withholding among users in virtual academic communities is influenced by multiple factors at both individual and environmental levels, leading to various configuration patterns. Knowledge power remains the primary factor contributing to high knowledge withholding among users in online academic communities. (2) Different combinations of high knowledge withholding are observed in virtual academic communities of different disciplines. In science and engineering communities, knowledge power, psychological ownership of knowledge, and subjective norms of knowledge withholding play major roles, while the influence of knowledge power is more widespread and direct in management communities, with less impact from psychological ownership. In medicine communities, individual factors often interact with community reciprocity and privacy protection at the environmental level. (3) The results of this mixed research method are mutually validating and complementary, providing more comprehensive conclusions. The study enriches and expands theoretical and methodological research on knowledge withholding in virtual communities, and provides insights for addressing knowledge withholding issues and promoting knowledge sharing in virtual communities.

[Purpose/Significance] With China’s rapid advancement in scientific and technological capabilities and growth of global influence, competition in science and technology among major countries will undoubtedly become an inevitable and constant challenge in China’s scientific and technological progress. Scientists are the strongest endogenous force to promote the development of national competitiveness. [Method/Process] Based on the biographies and other qualitative materials of Nobel laureates in the natural sciences, this paper adopted the grounded theory and a life course perspective to study the factors influencing top scientists mobility. It comprehensively and systematically revealed the key factors and the mobility path. [Result/Conclusion] External factors influencing scientists’ mobility include research demand, knowledge environment, economic demand and international situation. Internal factors include family life and personal factors. Both external and internal factors can affect the flow intention of scientists through direct paths, and external factors can also affect scientists’ choices through indirect paths. Based on scientists’ country of birth at the time of the award, factors influencing their mobility differ between the loss group and the non-loss group. Finally, this paper obtains implications and puts forward suggestions from five aspects: investment in science and technology, innovation culture, assessment system, social security and emotional identification.

[Purpose/Significance] The Altmetrics data generation process is explained from the perspective of information behavior. Based on this, discovering, identifying and digging out the main dilemmas in the development of Chinese Altmetrics can provide important references and practical guidance for fostering the application scenarios of Altmetrics in Chinese academic ecology. [Method/Process] Taking the process of Altmetrics proposal and connotation transmutation as the logical starting point of the research, this paper analyzed the generation process of Altmetrics data from the perspective of user information behavior, and combined the special characteristics of Chinese online social platform environment. It summarized the development dilemmas of Chinese Altmetrics and put forward corresponding countermeasure suggestions. [Result/Conclusion] Altmetrics data is the result of the information behavior of various stakeholders relying on network platforms. On the one hand, it reflects the accumulation of data in each stage of the life cycle of a single user’s information behavior, and on the other hand, it reflects the synergistic and overlapping emergence process of the information behavior of a large number of stakeholders centered on the network platform. The alienation of scientific communication function is the main reason for the predicament of Chinese Altmetrics development, which is centrally manifested in: the lack of endogenous motivation for Altmetrics development, the lack of consensus among the relevant stakeholders for Altmetrics development, and the lack of data aggregation tools for Altmetrics development. Countermeasures can be taken to break through the Altmetrics development dilemma by building multiple incentives and synergistic mechanisms, strengthening consensus and collaboration, and building an intelligent data integration and analysis platform.

[Purpose/Significance] Library consortia are currently facing slow development and weakened services. “Reconstruction,” as an effective solution for the smart transformation of library consortia, can drive them to form new service models and technical solutions. The reconstruction can help meet the growing demands of users and society for information and knowledge by building specific implementation processes. [Method/Process] This paper employed literature review and case analysis to outline an implementation pathway for smart library consortium reconstruction. It analyzed cases of smart library consortia, discussed potential implementation paths for their reconstruction, and provided a basis for improvement and refinement. [Result/Conclusion] Based on next-generation library service platforms, the smart reconstruction of library consortia can be achieved through several key areas: system selection, personnel allocation, service design, migration, and maintenance. Detailed migration plans for member libraries are essential, alongside a broader alliance strategy. Future efforts should be further emphasized technological innovation and collaborative alliance endeavors.

[Purpose/Significance] The development of the metaverse presents transformative opportunities and innovative pathways for the field of archival digital narrative. By focusing on the deep integration of the metaverse and archival digital narrative, exploring a layered framework and implementation pathways can provide theoretical references and practical guidance for metaverse-based archival narrative. [Method/Process] Based on the feasibility and necessity of constructing an archive metaverse and from the perspective of data-driven approaches, this paper comprehensively applied literature research and system analysis method to propose the framework of archive metaverse hierarchical development for digital narrative and the corresponding implementation path. The validity and feasibility of archive metaverse were verified through the case study of narrative development of founding generals’ archives in the Red Archives Resource Bank of Hubei Province. [Result/Conclusion] The hierarchical development framework of archival metaverse for digital narrative includes the data infrastructure layer, data integration layer, data representation layer, and digital narrative layer. It needs to be effectively implemented through a multidimensional synergistic path of co-construction.

[Purpose/Significance] With the rapid development and comprehensive application of digital technology, the importance of resilience has become prominent. Research on the digital resilience of librarians can better adapt to the needs of digital transformation of libraries, and has practical significance and value. [Method/Process] This study reviewed current research on digital resilience, defined the key characteristics of librarians’ digital resilience, constructed a logical model, and explored its mechanisms. [Result/Conclusion] This paper proposes the following strategies for the cultivation of librarians’ digital resilience: enhancing the hierarchy of librarians’ digital resilience cultivation, strengthening the structural connotation of librarians’ digital resilience, focusing on the coordination of multiple subjects and the construction of digital ethics, promoting the digital infrastructure construction and service risk avoidance of library, and cultivating independent development scenarios and resource support for librarians’ digital resilience. It provides useful references for further research and practice of librarians’ digital resilience.

[Purpose/Significance] Technology evolution path research has become an important reference for enterprise technology research and development decision-making. Currently, related studies focus on the relationships among common categories, co-occurrence, references, themes, and evolution but lack the in-depth exploration of causal links, especially the analysis of the mutual influence among technological events. The paper introduces the event graph and the event evolutionary graph driven by causal logic, aiming to explore the deepening causal process in the technology evolution path and analyze the complex correlation mechanism among technological events. [Method/Process] Based on ChatGLM, the paper designed prompt commands, extracted pairs of causal events from patents and scientific papers, constructed the causal event graph and the causal logic-based event evolutionary graph, and then formed coupled causal networks. The dynamic planning method and the weighted centrality algorithm were used to identify and quantify technological evolution paths and their events based on the event graph. Furthermore, the synergistic mechanism of the event graph and the event evolutionary graph were applied to the weighted influence analysis, and an innovative method for calculating the influence between pathway events was proposed. [Result/Conclusion] Causal association provides a way to reveal the influence and driving mechanisms in the process of technological evolution, which not only presents the multi-directionality and complexity of technological evolution paths but also lays the foundation for an in-depth interpretation of the interactions between path events.

[Purpose/Significance] Data is a key production factor of the digital economy. How to release the value of data elements has become a hot topic in academia and industry. As an important mechanism to release the value of data elements, the transfer and transformation of data are proposed to provide theoretical support and a practical path for data elements’ valorization through the systematic interpretation of the three dimensions of practical origin, conceptual connotation, and theoretical framework. [Method/Process] Based on the practical dilemma of releasing the value of data elements, this paper explained the necessity of transfer and transformation of data. This article defined the concept of transfer and transformation of data and clarifies its connotation by examining the technological evolution process. Finally, it combined the three-rights division and the whole life cycle of data, and formed a systematic theoretical framework for the transfer and transformation of data. [Result/Conclusion] This paper constructs an integration framework for the transfer and transformation of data from its realization mechanism, to answer the questions of “Why do data need to transfer and transform”, “What is the transfer and transformation of data”, and “How to transfer and transform data”, and to provide referable research ideas and entry points for future research.

[Purpose/Significance] This study examines the global developing trends of scientific data platforms, focusing on the characteristics of their growth in number, geographic distribution, and disciplinary distribution. The aim is to provide reliable reference for the construction and development of scientific data platforms, thereby promoting data sharing and open science. [Method/Process] This research involved writing program codes to access the application programming interfaces (APIs) of three registry platforms: re3data, OpenDOAR, and ROAR. The stored scientific data platform records were retrieved and subsequently processed and analyzed. [Result/Conclusion] The data analysis reveals that the number of global scientific data platforms has grown rapidly since 2000, though the growth rate has fluctuated. The distribution of scientific data platforms is concentrated in developed countries. Among the disciplinary categories, the humanities and social sciences account for the largest proportion, while the other three categories are relatively balanced. Additionally, the study conducts cross-analyses on the age of scientific data platforms in relation to their geographic and disciplinary distributions, further elucidating the development characteristics across different countries and academic fields.

[Purpose/Significance] Inter-organizational data sharing (IDS) is a powerful engine in the era of digital economy. It is of great significance to explore the barriers that exist in the practice of inter-organizational data sharing in China. [Method/Process] Based on the perspective of territoriality theory, this paper took the government data-sharing practices in three cities in central China as examples to conduct a case study. 37 territorial barriers were identified belonging to the three categories: organizational psychological cognition, organizational environment and organizational territorial behavior. A model of territorial barriers was constructed to IDS, and the logical relationship among the barriers was clarified based on the results of the case study. [Result/Conclusion] It finds that six types of territorial behaviors: territory establishment, identity-oriented marking, control-oriented marking, anticipatory defense, reactive defense, and territorial expansion, play an obstructive role in different stages of IDS. In addition, the results of the study show that the effects of organizational psychological cognition and organizational environmental barriers on different territorial behaviors are particularly focused, providing ideas for proposing feasible solutions to alleviate the territorial barriers to IDS in China.

[Purpose/Significance] Through the quantitative analysis and evaluation of the existing policies in China, it provides a basis for the formulation, adjustment and improvement of healthcare big data policies in the next stage. [Method/Process] Taking 103 policies from the central and provincial governments in China as research objects, this paper constructed a three-dimensional analysis framework of “theme-tool-effectiveness”, and applied LDA theme modeling, content analysis method and PMC index model in order to conduct multi-dimensional mining and systematic analysis of policy texts. [Result/Conclusion] The policy themes cover a wide range and include openness and protection. The structure of policy tools is unbalance, and the combination needs to be optimized. The overall policy effectiveness is acceptable, with a large gap between levels. Finally, policy optimization suggestions are put forward in terms of enriching policy themes and details, optimizing the combination of policy tools, promoting the proliferation of high-quality policies, and encouraging public participation.

[Purpose/Significance] To investigate the influence mechanism and boundaries of data assetization on the new quality productive forces in enterprises through quantitative analysis can provide theoretical insights for enterprises to develop new quality productive forces and achieve high-quality growth. [Method/Process] This article took the strategic emerging industries listed on the China’s A-share market from 2010 to 2022 as research objects, and analyzed the impact of enterprise data assetization on enterprise new quality productive forces by quantifying the latter. [Result/Conclusion] Data assetization can significantly improve the development level of new quality productive forces of enterprises. After a series of robustness tests, such as instrumental variables, the results remain robust. At the same time, through heterogeneity analysis, it finds that the promoting effect of data assets on new quality productive forces is more pronounced in small-sized and state-owned enterprises. In addition, data assets not only improve the level of new quality productive forces of enterprises by alleviating financing constraints but also enhance it by improving the quality of internal control and the collaboration efficiency with upstream and downstream supply chain enterprises. This article provides empirical support for clarifying the path and boundary of the role of data assetization in enhancing new quality productive forces of enterprises, and can also provide policy basis for fully realizing the value and potential of data elements in China.

[Purpose/Significance] This study designs indicators to measure the novelty of a scholar’s early knowledge structure based on the innovative characteristics inherent in it. The purpose is to predict the scholar’s future influence, thereby providing new indicators for the early identification of academic talents. [Method/Process] Firstly, a dataset of 59,207 scholars in the biomedical field was obtained from the PubMed knowledge graph (PKG) database, and the knowledge structure of scholars was constructed using the co-occurrence relationships of controlled subject terms. Secondly, 6 indicators were designed to measure the novelty of scholars’ early knowledge structures on two levels: knowledge units and structural positions. Then, scholars were classified and labeled based on their later influence, and some machine learning models were trained. Finally, the classification effectiveness of different models was evaluated using the combination variable method, and the predictive performance of indicators based on the novelty of knowledge structures was analyzed. [Result/Conclusion] The study finds that novelty indicators can effectively predict influence. Among single-indicator predictions, topic novelty (TN) performs the best, while the 4 structural indicators all outperform the topic combination novelty (TCN). The F1 value of the comprehensive indicators is improved by an average of 2.7%. The novelty of knowledge structures provides a perspective for predicting and understanding scholars’ academic influence from content characteristics. The indicators designed are valuable and can complement existing prediction indicators.

[Purpose/Significance] This paper systematically reviews the practice and implementation path of citizen science in the UK, and provides reference for promoting citizen science practice in China. [Method/Process] Through searching the official websites of the British government, research institutions, research funding institutions and citizen science organizations, this paper comprehensively expounded the present situation of citizen science practice in the UK from four aspects: citizen science policy documents, infrastructures, projects and evaluation methods, and summarized the implementation path of citizen science in the UK and its enlightenment to China. [Result/Conclusion] The development of citizen science in the UK is a world leader, forming a spiraling path of citizen science implementation including making citizen science policy planning, planning citizen science projects, implementing citizen science projects, and carrying out citizen science evaluation and feedback. China can learn from the successful experience of UK citizen science, strengthen the top-level design of citizen science, give full play to the role of citizen science stakeholders, strengthen the evaluation and feedback of citizen science, and promote the professional development of citizen science.

[Purpose/Significance] Minors, as a key group in national reading, are highly valued by society. And the relevant research shows obvious characteristics of interdisciplinary integration. This article reviews existing achievements, clarifies the trend of cross-integration in research on minors reading, and provides reference for future theoretical expansion and practical development. [Method/Process] In terms of China National Knowledge Infrastructure (CNKI) as the data source, BERTopic modeling technique was employed sequentially to identify topics, cluster topics, and display trends of research results. The topic contents and causes of changes were analyzed step by step from shallow to deep, and future research recommendations were proposed. [Result/Conclusion] Research on minors reading in China has formed 15 research topics from now on, which can be clustered into five major topic groups: reading promotion, early reading, social reading, reading literacy, and dyslexia. In 2006, 2012, 2015, and 2018, there were significant changes in the intensity of research, influenced by three major factors: national policy advocacy, basic rights protection, and technological transformation requirements. Future research needs to continue to combine interdisciplinary research paradigms, focus on reading promotion, social reading, and dyslexia, and conforms to the requirements of national and era transformation.

[Purpose/Significance] Scientific data serves as a pivotal strategic asset for driving national technological innovation and propelling socio-economic progress. Evaluating the value of scientific data is crucial for unlocking its potential, augmenting its utility, and fostering the advancement of open science. [Method/Process] Firstly, scientific data was taken as the research object. Based on theories of data lifecycle and value enhancement, the factors and mechanisms affecting scientific data value at each node in the value co-creation chain were analyzed. Secondly, a scientific data value evaluation system was constructed across three dimensions: fundamental value, academic value, and open-sharing value. The weights of various indicators were determined using the analytic hierarchy process (AHP). Finally, the evaluation system was validated through experiments with datasets from the National Tibetan Plateau Data Center. [Result/Conclusion] The proposed scientific data value evaluation system can effectively evaluate the value of scientific data and provides theoretical guidance and practical implications for the scientific data management, opening and sharing, and the development of related policies. This contributes to enhancing and efficiently utilizing the value of scientific data and advancing the development of open science.

[Purpose/Significance] The development of generative artificial intelligence has sparked a new round of social anxiety. As the discipline of information resource management is closely related to this technology, students are more susceptible to various forms of anxieties. [Method/Process] The study, based on the theory of fear acquisition and the structural model of technological fear generation, constructed a structural model of generative artificial intelligence anxiety among students in the information resource management. Utilizing a questionnaire survey method, the research investigated three dimensions of anxiety: learning anxiety, employment anxiety, and environmental anxiety. It also analyzed the influencing factors of artificial intelligence anxiety. [Result/Conclusion] Students in the Information Resource Management generally experience AI anxiety, with employment anxiety being the most severe. The level of the university and the student’s rural background significantly influence their anxiety levels. Students from higher-level universities and rural areas tend to experience greater anxiety. Discrepancies between curricula and intense competition exacerbate learning anxiety, while the potential displacement of jobs by generative AI contributes to employment anxiety. There is an urgent need to create a social environment that promotes the development and utilization of generative artificial intelligence.

[Purpose/Significance] This paper recommends different viewpoints within user’s acceptable range to generate resolution path of online opinion disagreement and reduce the risk of polarization. [Method/Process] Firstly, this study identified views through text clustering and sentiment analysis. Secondly, it determined whether a comment represented acceptance based on recognizing the object of a comment, calculating topic similarity between the post and the comment, and sentiment analysis. Then, it calculated users’ polarity and the degree to which users could accept different viewpoints, based on which a resolution path of online opinion disagreement was generated. [Result/Conclusion] The Sina Weibo platform is chosen as the data source. It proposes a set of rules to determine whether a comment represents acceptance, with a F1 score of 0.8911. This study provides a possible path for resolving controversy, which can achieve the extension of recommended users to different viewpoints. The resolution path of online opinion disagreements proposed in this study may be able to provide some reference for public opinion governance in crisis situations.

[Purpose/Significance] This research explores the evolutionary process of users’ health anxiety relief through health science popularization short videos, and aims to provide countermeasures for the health information service of such videos and the self-health management of users with health anxiety. [Method/Process] Empirical data on users’ health anxiety relief through short videos were collected through semi-structured interviews. By applying interpretative phenomenological analysis, four mechanism evolution paths were identified: attention triggering, supply-demand coupling, cognitive regulation, and relief interaction. Additionally, the internal relationships between the evolution and mechanism were systematically elucidated. [Result/Conclusion] Based on the research on the evolution mechanism of health anxiety relief through health science popularization short videos, this paper proposes management strategies for alleviating users’ health anxiety from the perspectives of short video platforms, science popularization subjects, and users with health anxiety. These strategies focus on addressing health knowledge supply and demand, aiming to provide a reference for mitigating users’ health anxiety.

[Purpose/Significance] Exploring the efficacy of current bibliotherapy on depression and anxiety of university students and analyzing factors potentially influencing intervention effects, can provide evidence-based evidence for related studies, and further obtain implications for improving the effectiveness of empirical research on bibliotherapy. [Method/Process] Evidence-based systematic review and meta-analysis were used to comprehensively analyze the selected experimental intervention results based on the random effects model. [Result/Conclusion] Bibliotherapy has a certain effect on depression and anxiety symptoms of university students. The intervention effect of interactive bibliotherapy is more significant than that of self-help bibliotherapy compared with the control group. However, the current empirical research on bibliotherapy has some limitations in terms of intervention methods, book compatibility, randomized experiment design and literature quality. Future studies can improve the effectiveness of bibliotherapy through the interaction of intervention measures, evidence-based intervention books, professionalization of implementers, research design and standardization of writing.

[Purpose/Significance] Clarifying the value co-creation mechanism of open public data is of great significance for unleashing the value of open public data and creating a value co-creation ecosystem. [Method/Process] Through literature research, Mitchell scoring method, relevant stakeholders were identified and classified. Then, from the perspective of supply and demand matching, the value behavior and relationships of each stakeholder were analyzed. Based on this, a two-dimensional analysis framework of “horizontal implementation process — vertical collaboration process” was constructed to reveal the value co-creation mechanism. [Result/Conclusion] The study finds that there are 10 stakeholders involved in the value co-creation of open public data, which can be divided into three categories based on their level of participation: core, sub core, and peripheral stakeholders. From the perspective of horizontal implementation process, each stakeholder undergoes activation, aggregation, and diffusion of data value to achieve value co-creation. From the perspective of vertical collaboration level, each stakeholder goes through the service exchange layer, resource interaction layer, and reaches the value co-creation layer.

[Purpose/Significance] This paper explores the key influencing factors and mechanism of algorithm literacy on users’ adoption behavior of recommended information, aiming to provide a theoretical basis and practical guidance for improving the user experience and user adoption of algorithm recommendation. [Method/Process] Based on the FATE model and self-efficacy theory, a theoretical model of the influence of algorithm literacy on users’ adoption behavior of recommended information was constructed, and empirical analyses were conducted with SEM and fsQCA. [Result/Conclusion] The SEM results indicate that algorithm perception and its sub-dimensions, algorithm skills, and algorithm literacy self-efficacy have a significant influence on users’ adoption behavior of recommended information, while the algorithm knowledge does not. The fsQCA analysis reveals 8 configurations that positively affect users’ adoption behavior, indicating that the constituent elements of algorithm literacy need to work synergistically to be effective. Among them, perceived algorithmic transparency, perceived algorithmic fairness, algorithm skills, algorithm knowledge, algorithm literacy self-efficacy, and adoption attitude are the key factors contributing to users’ adoption behavior.

[Purpose/Significance] Evaluating the maturity level of smart library development in universities is crucial for the self-reflection on the effectiveness of smart library and the formulation of future development plans. [Method/Process] This paper designed a sampling questionnaire based on the maturity evaluation model of smart library development of universities. It selected 21 public universities in Beijing to obtain index data through questionnaire survey, and carried out an empirical evaluation of smart library development of universities. [Result/Conclusion] The development of smart libraries in universities in the capital is in the developing stage. Each library presents different characteristics in the dimensions of librarian team, infrastructure, business management and user service. According to the results, the paper puts forward the optimization suggestions for specific construction contents in each dimension from the micro perspective, and proposes maturity level improvement strategies from the initial level to the optimization level from the macro perspective.

[Purpose/Significance] The knowledge element database is constructed by integrating the potential multidimensional relationship between South China Sea rights protection evidence, which can represent the massive evidence and its association in a deep and all-round way. In turn, it provides large-scale, high-quality, and fine-grained annotated corpus to support the construction of an evidence chain for South China Sea rights protection. [Method/Process] First, considering the existing knowledge element database and based on the knowledge element representation and linking theories, facing the needs of evidence chain construction, this paper proposed a theoretical framework for an evidence knowledge element database for South China Sea rights protection and deeply explained the core content of evidence knowledge element representation and evidence knowledge element association. Second, based on this theoretical model, the construction path of the knowledge element database was proposed. The evidence knowledge elements were modeled in stages from shallow to deep in the carrier layer, content layer, value layer, and association layer, and integrated into a knowledge element database through the four sub-databases. Third, some text and map evidence knowledge elements were selected to verify the feasibility of the proposed theoretical framework and realization path. [Result/Conclusion] It can provide a reference for the relevant research on the South China Sea document collection, knowledge element database, and the evidence chain for South China Sea rights protection. The knowledge element database for scaled multidimensional South China Sea rights protection evidence needs further research and implementation.

[Purpose/Significance] In the context of interdisciplinary integration, analyzing and grasping the current situation and future direction of interdisciplinary output influence of disciplinary knowledge is conducive to promoting the development of discipline and improving the academic discourse power. [Method/Process] The interdisciplinary citation sentence is the intermediary “bridge” connecting the output knowledge with the received knowledge. On one hand, their semantic expression can reflect the closeness of the relationship between the two disciplines. On the other hand, their location and emotional tendency can reflect the different stimulating effect and the discipline knowledge value on interdisciplinary knowledge innovation. This paper constructs an influence model of a target discipline knowledge on interdisciplinary knowledge from two aspects: knowledge relevance and knowledge innovation efficiency. The output of one knowledge has an impact on multiple interdisciplinary knowledge, so the overall influence is calculated by summing, simultaneously identifying the output knowledge of the target discipline and the influenced interdisciplinary knowledge. [Result/Conclusion] Taking the data of Information Resource Management discipline from 2017 to 2022 as an example, the validity of the model is verified. It finds that knowledge of this discipline mainly influences the knowledge innovation in social sciences, with less impact on natural sciences. The influence of mature cross-knowledge is stronger than that of professional core knowledge. It mainly affects interdisciplinary knowledge, being less effective in influencing the core knowledge innovation of other disciplines.

[Purpose/Significance] This study aims to improve automatic sentence segmentation and punctuation in ancient Chinese texts using generative large language models, overcoming the limitations of traditional sequence labeling models that require specialized label design and annotated data construction. [Method/Process] In order to increase the number of learnable samples, a sliding window strategy was used to segment training data. Additionally, MinHash and Locality-Sensitive Hashing (LSH) were employed to provide reference samples for unpunctuated texts, and constraints were applied to the decoding process of the large language model. The Xunzi ancient literature large language model served as the base model. Fine-tuning was performed using Low-Rank Adaptation (LoRA) to align the model with the task of ancient Chinese automatic punctuation, enabling the generation of target texts with punctuation from unpunctuated texts. [Result/Conclusion] On two benchmark datasets released by EvaHan 2024, the F1 scores of automatic sentence segmentation are 88.47% and 92.48%, and the F1 scores of automatic punctuation are 75.29% and 80.01%, respectively. These results significantly outperform the Xunzi ancient large language model and ChatGPT 3.5, indicating that generative large language models are a feasible approach for addressing the tasks of sentence segmentation and punctuation in ancient Chinese texts.

[Purpose/Significance] With the rapid growth of short videos and the increasing number of users, the personalized recommendation algorithms widely adopted by short video platforms improves the user experience, but also brings the problem of users’ information homogenization, which in turn restricts the breadth and depth of users’ information acquisition. The purpose of this study is to explore users’ circle-breaking behavior on short video platforms, specifically how users break through their existing video preferences, in order to provide users with a more diversified and comprehensive information acquisition experience, and promote the healthy development of short video platforms. [Method/Process] This study combined the method of theoretical construction and empirical research, taking Kuaishou short video platform as a case study. The AIS model of user behavior analysis was proposed, which was used to segment users and analyze their circle-breaking behaviors and willingness. At the same time, based on the large language model technology, a recommendation system architecture was designed to assist users to break the circle, aiming to promote users’ information diverse exploration by technical means. [Result/Conclusion] Kuaishou users can be subdivided into four categories. Each of them shows different characteristics in their video consumption and social interaction. Overall, users show a low willingness to leave their original preferred videos and actively choose new ones. However, it is worth noting that users who are active on social networks but do not frequently consume or interact with specific content are more likely to exhibit circle-breaking behavior. Therefore, leveraging platforms and algorithms to assist users in breaking the circle is an important way to enhance user experience and promote the healthy development of platforms.

[Purpose/Significance] Analyzing the user participation patterns in online health communities from a symbiosis theory perspective can help understand the complex interactive relationships in these communities and provides references for improving their management mechanisms. [Method/Process] Firstly, representative data of user participation in Zhihu’s health communities were selected and coded on the grounded theory to identify the behavioral patterns of user participation. Secondly, based on symbiosis theory, the patterns of user participation in online health communities were constructed, exploring the roles, motivations, paths, and modes of user participation in symbiotic scenarios. Finally, combining different modes of user participation, the symbiotic states and behaviors of users were analyzed from a dynamic perspective. [Result/Conclusion] Under the dual effects of self-organization and hetero-organization, the roles of lurkers, bystanders, creators, and evaluators intersect in online health communities along consumption-driven, creation-driven, and interaction-driven paths, generating singular, diverse, and interactive modes of participation. User symbiotic states initially transition from parasitism and biased parasitism to asymmetrical mutualistic relationships, then to mutualistic relationships, ultimately achieving a balance between conflict and cooperation in online health communities.

[Purpose/Significance] Based on the perspective of user experience, this paper reveals the processing path of social media information credibility judgment, and the influence of perceived information load, emotional valence of information content, topic familiarity and comment attitude on their credibility judgment. It can provide some ideas for the management of online false information. [Method/Process] Based on ELM theory, 2*3*2 scenario experiment was adopted, and data were recovered by network questionnaire (N=791). Statistical methods such as T-test and regression analysis were used to analyze the data. [Result/Conclusion] Compared with UGC with low information load, users have higher perceived credibility for UGC with high information load. Compared with positive UGC, users have higher perceived credibility for negative and neutral UGC. A significant interaction effect exists between perceived information load and the emotional valence of UGC. Negative comments can significantly reduce user perceived credibility. For highly familiar topics, positive comments significantly reduce the perceived credibility of negative and emotionless content. For less familiar topics, positive comments significantly reduce the perceived credibility of emotionless UGC.