[Purpose/Significance] This study aims to analyze the formation mechanisms of information cocoons and explore pathways to break through them, providing users with scientific strategies for overcoming these barriers. [Method/Process] The paper began with the fundamental scenarios of information acquisition and incrementally introduced influencing factors, constructing an integrated model of "formation-evolution-breakthrough" for information cocoons. Simulations were conducted on three scenarios that users might encounter: information acquisition rate, cocoon-breaking choices, and attitudes towards breakthroughs, yielding simulation conclusions with guiding value for breaking through information cocoons and providing mathematical support for users to formulate scientific strategies. [Result/Conclusion] The research finds that moderately slowing down the rate of information acquisition helps users break through information cocoons. Actively embracing external interventions is beneficial for broadening users' channels of information perception, thereby assisting them in overcoming information cocoons; cognitive factors are key to achieving breakthroughs, and users should actively enhance their cognitive levels. Personalized recommendation algorithms have a dual impact on information cocoons, potentially exacerbating the polarization of information. Therefore, users should adopt a proactive stance, using recommendation algorithms as tools to verify their cognitive reflections, which in turn can aid them in breaking through information cocoons.

[Purpose/Significance] Precision is the goal of the development of community elderly care services and an important standard for measuring the level of community elderly care services.There is a supply-demand contradiction in the current development of community elderly care services, and the level of precision needs to be improved.The rapid development of digital intelligent environments such as big data and artificial intelligence has brought historical opportunities to improve the precision of community elderly care services, and research and exploration of the influence mechanism on the precision level of community elderly care services is a prerequisite for improving the precision of services. [Method/Process] Based on the value-network model, the grounded theory research method was used to conduct coding analysis on the semi-structured survey interviews with representatives of relevant participants in community elderly care services with reference to the classic grounded theory paradigm of"context-conditions-action-results", and the influence mechanism of value-network on the community elderly care precision services in digital intelligence environment was researched. [Result/Conclusion] A"Rocket Model"of the influence mechanism is constructed to analyze the influencing factors and mechanism of value-network on the precision of community elderly care services from three levels: macro, meso and micro.Among them, "Digital Intelligence Technology Empowerment"is the key influencing factor.The study answers the question of "what is the influence mechanism of value-network on community elderly care precision services in the digital environment", and points out the direction for further exploration of specific strategies to improve the precision level of community elderly care services.

[Purpose/Significance] This study investigates the interdisciplinary patterns of outstanding scientists from the perspective of academic careers, aims to provide certain insights for individual interdisciplinary pattern selection and the development of disciplinary integration. [Method/Process] Taking the winners of Derek de Solla Price Memorial Medal, the highest award in the field of scientometrics as examples, this study examined their interdisciplinary patterns from two dimensions-publication of papers and sources of knowledge. It delineated their academic careers into four stages-incipient, growth, deepening and maturation-to analyze the evolutionary features of their interdisciplinary patterns. [Result/Conclusion] This study identifies four types of scientists with distinct interdisciplinary patterns-amphibious scientists, indigenous scientists, immigrant scientists and resident scientists. Scientists from these categories exhibit differentiated interdisciplinary performance across various stages of their academic careers. They have made outstanding contributions to the development of scientometrics at different periods.

[Purpose/Significance] As an important driving force for the innovative development of humanities and social sciences, Interdisciplinary/Integrated Studies is an inevitable way to solve complex problems. As an important carrier of cross-research, the Interdisciplinary/Integrated Research Program in Humanities and Social Sciences of the Ministry of Education has played an active role in promoting cross-research in humanities and social sciences in recent years, and aims to provide useful insights and references for future cross-research in humanities and social sciences through the research. [Method/Process] This study systematically analyzed 4045 Interdisciplinary/Integrated research projects funded by the Ministry of Education (MOE)over the past decade(2014—2023)using a combination of quantitative and qualitative methods to explore the number of projects, types, their distribution, research topics, and trend. [Result/Conclusion] The study found that interdisciplinary research in the humanities and social sciences has grown steadily in both quantity and depth, and the research topics cover a wide range. Important research hotspots have emerged in Urban and rural social development and special group issues, environmental protection and sustainable development, regional economy and industrial transformation and upgrading, cultural heritage and innovative development, artificial intelligence and information technology application, mental health and educational innovation. It also introduces the integration of multiple disciplines, combining empirical research and theoretical exploration, focusing on real problems, and giving equal importance to innovation and practicality as the characteristics of cross-cutting research.

[Purpose/Significance] To address the issues of insufficient datasets and difficulty in cross-domain transfer in Chinese aspect-based sentiment analysis (ABSA), the paper explores the application and performance of Chinese large language models in ABSA tasks. [Method/Process] The paper utilized the ChatGLM model, employing prompt engineering and fine-tuning techniques of LoRa and P-Tuning, to conduct ABSA tasks on the Chinese open aspect-level sentiment analysis dataset, ASAP. [Result/Conclusion] Compared with baseline models, ChatGLM based on few-shot prompts has performance close to that of full-sample deep learning models, while models combined with LoRa and P-Tuning achieve the best results and show good classification ability in the actual ASAP dataset.The paper verifies the effectiveness and feasibility of aspect-based sentiment analysis of Chinese large language models in the Chinese context and provides new solutions and references for the field of Chinese ABSA.

[Purpose/Significance] The digital economy policy has become an important policy tool for the government to promote economic development, and an empirical analysis of the effectiveness of China's local digital economy policy implementation can be helpful to promote the local economy to achieve high-quality development. [Method/Process] This paper examined the impact of local digital economic policies on regional economic development using the PSM-DID method with panel data from 337 prefecture-level and above cities in China from 2010 to 2021. [Result/Conclusion] Local digital economic policies significantly promote regional economic growth.However, their promotional effects exhibit a two-year time lag.The implementation of digital economic policies proves to be more effective in cities with larger population sizes or higher administrative levels.Additionally, the impact of digital economic policies on regional economies in central and western regions exceeds that in eastern regions.

[Purpose/Significance] Simulation based on system dynamics can comprehensively capture the dynamics of complex social systems under the influence of policies, accurately simulate the cumulative impact of policy interventions over time, and evaluate the implementation effect of policies, which plays an extremely important role in promoting the scientific and efficient formulation and use of policy tools and improving the effectiveness of policies. [Method/Process] Taking the implementation of fertility policy as an example, based on key influencing factors such as fertility rate and environmental influencing parameters such as education and economy, this paper constructed a simulation system based on system dynamics through Vensim PLE.The model dynamically demonstrated the interactions between the population—policy—economy subsystems and designed and implemented three differentiated policy intervention scenarios, and conducted in-depth simulations to predict the paths of demographic change and the evolutionary trends under different policy orientations. [Result/Conclusion] It is found that the liberalization of fertility policies had effective in mitigating the ageing trend while promoting population growth.However, the impact of the policy is waning and structural changes and adjustments are urgently needed.

[Purpose/Significance] Improving scientific data ethics governance can help regulate the scientific data collection, sharing and use, bring into the function of data as a key resource and element in research, and optimize scientific data management services. [Method/Process] This study analyzed the scientific data ethics policy using the UK as an example based on the Grounded Theory, summized the policy framework and content, revealed the governance characteristics through matrix coding and Social Network Analysis, and put forward suggestions for the scientific data ethics governance in China. [Result/Conclusion] Results indicate that the scientific data ethics policy framework includes 3 dimensions: the environment, subject and strategy.The environment involves applicable fields, subjects, concept definitions, problem analyses, and existing policies.The subject consists of the definition of governance subjects and collaboration promotion.The strategy includes governance guidance and measures at various stages.Accordingly, this research proposes four pathwayes: forming an ethical governance system, standarizing the ethical theory, clarifying the governance rights and responsibilities of all parties and the way of collaboration, and refining the ethical governance at all stages.

[Purpose/Significance] Analyzing the continuance use intention of generative AI college student users can provide theoretical references for optimizing the generative AI user experience and enhancing the new quality productive forces of the society. [Method/Processes] The article constructed the influencing factors model of generative AI college student users' continuance use, which was based on expectation confirmation theory and use and gratification theory, and took college students from five colleges and universities in Hangzhou as the research object, collected data through the questionnaire survey method, and verified the variables and hypotheses in the model by using SPSS 27.0 and AMOS 27.0. [Result/Conclusion] The study shows that: satisfaction is a key influencing factor on college student users' continuance use intention, and the factors of information quality, system quality, pleasure satisfaction, utilitarian satisfaction, and other factors have a significant direct positive effect on college student users' continuance use intention, and the expectation of confirmation, information quality, system quality and other factors can have a significant indirect positive effect on college student users' continuance use intention through satisfaction.

[Purpose/Significance] Against the backdrop of frequent public health incidents, the demand for health information among the public is growing rapidly.Social media as an important way for users to obtain information, not only efficiently spreads health information, but also provides convenient conditions for the generation and dissemination of false health information.With the increasing penetration and influence of social media, users have a stronger sense of uncertainty about health information.In view of this, this article explores the mechanism of trust formation among social media health information users, in order to provide reference and inspiration for subsequent related research. [Method/Process] This paper deconstructed the elements that form user trust in social media health information, constructed a trust framework oriented towards user perception process, proposed a theoretical hypothesis model of user trust in social media health information from three aspects: user, information and environment, and then modified the structural model. [Results/Conclusion] The paper aims to clarify the process of perceived trust and psychological changes among social media health information users from a theoretical perspective.The paper also found that emotional polarity, involvement, source credibility, and conflict resolution have a significant positive impact on trust in hot reviews.Trust has a significant positive impact on adoption intention.Reference group norms have a significant positive impact on adoption intention.Trust plays a complete mediating role between emotional polarity, involvement, source credibility, and conflict resolution and willingness to adopt information in hot reviews.

[Purpose/Significance] Current mainstream recommendation algorithms based on knowledge graph mainly focus on mining and utilizing item-side knowledge, paying less attention to user-side auxiliary information, leading to issues such as sparse user data and insufficient mining depth. [Method/Process] Addressing the structural and feature differences between user-side and item-side auxiliary information, the study proposed a dual-graph attention recommendation model that integrated social relationships and knowledge graphs. Firstly, the user social network graph and item knowledge graph were separately fused with the user-item interaction graph to obtain the user social relationship collaborative graph and item collaborative graph. Secondly, the study used a dual-graph attention network to process these two knowledge graphs separately, extracting different user and item feature vectors. Then, through the attention mechanism, the extracted user and item feature vectors were merged. Finally, the interaction probability of users and items was calculated using inner product operation for recommendation. [Result/Conclusion] The study conductes experiments on the Last-FM and Douban datasets, demonstrating that the model outperforms other baseline models on various datasets.

[Purpose/Significance] AI technology, exemplified by AI-generated content, facilitates the emergence of new quality productive force and multi-dimensional value implications, which can better assist China's digital economy to achieve high-quality development and better promote the innovation of knowledge and intelligence services in China. Analyzing the new mechanisms, risks, and paths of AIGC-enabled knowledge and intelligence innovation services holds significant theoretical and practical importance for promoting the vigorous development of the discipline of information resource management under the major national strategy of new productive force. [Method/Process] Based on the theoretical connotation of new quality productive force, the paper analyzed the internal mechanism of AIGC-enabled knowledge and intelligence service innovation from the perspectives of labor objects, laborers, and labor materials. It identified the risks of AIGC-enabled knowledge and intelligence service innovation from the three dimensions of information source, channel, and information receptor, based on the three elements of information transmission, and proposed governance strategies. The paper also explained the practical path of AIGC-enabled knowledge and intelligence innovation services from the perspective of the composition of new productive force. [Result/Conclusion] The paper shows that under the new quality productive force strategy, AIGC forms an internal mechanism for knowledge and intelligence service innovation. This mechanism relies on data elements, uses basic models for support, and features human intelligence collaboration as its core. The paper also indicates a need for better management of data privacy and security risks, cyberspace security risks, and scientific and technological ethics security risks. This requires leveraging the collaborative advantages of industry, academia, and research. This paper proposes a practical path for promoting AIGC-enabled knowledge and intelligence service innovation. This path involves constructing a new model driven by data elements, forming a new team centered on human-intelligence collaboration, and developing reliable and trustworthy intelligent models.

[Purpose/Significance] The study aims to explore the influencing mechanism of social media users' algorithm awareness on their self-concealment behavior, which is helpful to improve the multi-governance system of algorithm governance in China, and provide a theoretical reference for the privacy management of social media users. [Methods/Process] Based on Privacy Calculus Theory, this paper explored the influencing mechanism of algorithm awareness on social media users' self-concealment behavior, and considered the moderating effect of platform trust.By collecting questionnaires from 730 social media users, the empirical study was conducted by using structural equation model and Bootstrap method. [Results/Conclusion] The results show that algorithm awareness has significant positive effects on privacy concerns, perceived benefits, privacy risk belief and self-concealment.Perceived benefit has no significant effect on privacy risk belief.Privacy risk belief has a partial mediating effect between algorithm awareness and self-concealment.Privacy concern and privacy risk belief have a chain mediating effect between algorithm awareness and self-concealment.Platform trust negatively regulates the relationship between algorithm awareness and self-concealment.

[Purpose/Significance] As a passive behavior, users' intermittent discontinuance may make it difficult for generative AI to retain users and achieve a competitive advantage.Thus, it is necessary to examine the formation mechanism of user intermittent discontinuance and find the significant factors. [Method/Process] From a C-A-C perspective, this research examined the enablers and inhibitors of generative AI users' intermittent discontinuance.Enablers include privacy concern, information hallucination and cognitive dissonance, while inhibitors include intelligence, anthropomorphism, personalization and emotional commitment.SEM and fsQCA were adopted to conduct data analysis. [Results/Conclusions] Privacy concern and information hallucination affect cognitive dissonance, which further leads to intermittent discontinuation.Intelligence, anthropomorphism, and personalization affect emotional commitment, which prevents intermittent discontinuance.The results imply that generative AI needs to mitigate users' privacy concern and reduce information hallucination in order to lower cognitive dissonance.On the other hand, generative AI needs to enhance the intelligence, anthropomorphism, and personalization in order to increase users' emotional commitment and prevent their intermittent discontinuance.

[Purpose/Significance] This paper focuses on investigating the causes and mechanisms behind users' intention to avoid artificial intelligence-generated content (AIGC)information, aiming to provide theoretical guidance for user information behavior, optimization of AIGC technology, and iteration of AIGC products. [Method/Process] Drawing upon the C-A-C framework, this study constructed a theory model to examine the influence of controllable degree of information, transparency of information, and AI anxiety on information avoidance.The study collected sample data through virtual experimental design, and analyzed data using partial least square structural equation modeling (PLS-SEM). [Result/Conclusion] The findings reveal significant differences in users' avoidance intention towards AIGC information based on its transparency and controllability.Additionally, AI anxiety exhibits a positive relationship with information avoidance behavior.Notably, it is important to acknowledge that AI identity threat positively moderates the relationship between AIGC information uncertainty and AI anxiety.

[Purpose/significance] This paper conducted quantitative evaluation and analysis of national open science policies formulated by European countries, with a view to providing necessary reference for China to formulate and improve its open science policies. [Method/process] This paper firstly selected national open science policies formulated by 11 European countries as research objects, secondly conducted quantitative analysis from three perspectives: policy themes, policy tools and policy effectiveness, thirdly constructed the policy evaluation index system and PMC index model according above analysis results, then carried out quantitative evaluation and comprehensive analysis of open science policy texts of European countries, and finally put forward suggestions for promoting the practice progress of open science policy in China. [Result/conclusion] The overall evaluation result of national open science policies of 11 European countries is excellent, and the shortcomings and references are found through above policy evaluation analysis.It was suggested that China should refer to and learn from the advanced policy practices of European countries as soon as possible, strengthen the top-level design of open science policy at the national strategic level, coordinate multiple policy subjects to formulate an open science policy system, and comprehensively use various policy tools to promote the progress of open science policy practice.

[Purpose/Significance] The study aims to analyze the complicated relationship among the factors influencing the adoption intention of AIGC users under the scientific research scenario, and analyzes whether there is a single factor that has a necessary effect on the adoption intention of users, it provides theoretical and practical reference for the popularization and application of AIGC in scientific research scenarios. [Method/Process] The necessary condition analysis and fuzzy set qualitative comparative analysis were used to analyze 522 questionnaire data to explore the necessity of single factor and the adequacy of configuration path. [Result/Conclusion] The study finds that there is no single factor that has a necessary effect on the adoption intention of AIGC users, there are 11 high adoption intention paths and 4 low adoption intention paths in the influencing factors configuration paths.Among them, perceived quality, perceived usefulness, perceived ease of use, perceived task technology matching, perceived trust, social influence, and user expectation all play an important role in the configuration path as the core condition or edge condition.

[Purpose/Significance] Promoting the transformation of data elements into new quality productive forces has become an important issue for policy makers and practitioners, therefore it being of practical significance to analyze the rationality and scientificity of data elements policies. [Method/Process] Using the policy documents quantitative analysis method, this paper analyzed how policies promote the transformation of data elements into new productive forces.This paper used the following analytical framework: policy subject, policy tool, policy target, and the logic of the data element value chain: collection, storage, governance, transaction and application. [Results/Conclusions] This paper finds that: (1)The central policy entities are relatively scattered, and the local governments with developed digital economy have a significant driving role.(2)Supply side policy tools and environmental side policy tools are the main policy tools, with digital innovation, data application, data transaction, and data governance as the main policy targets.(3)There are some differences in the layout and combination of policy tools and policy targets between central and local governments.(4)To improve policy efficiency, the policy system can be optimized, such as the combination of policy subjects, policy targets, and policy tools, as well as the combination of universal and special policy tools.

[Purpose/Significance] Infant and toddler online health information is becoming an important support for infant and toddler parenting, this paper explores the behavioral pathways of infant and toddler online health information adoption of the new generation parents, and provides an informational perspective and theoretical framework for the understanding and analysis of Chinese parenting practice. [Method/Process] A semi-structured interview method was used to collect the behavioral practice experiences of 32 new generation parents on infant and toddler online health information. Based on the grounded theory, eight main categories of context, motivation, information, subject, family, society, usefulness perception and response were sorted out, and then a theoretical model of the behavioral path of relevant online health information adoption was constructed. [Result/Conclusion] It is found that under different circumstances, parents acquire, identify and adopt relevant infants and toddlers' online health information based on different motivations, so as to further strengthen their parenting views and practice. In this process, family and society, as an external system, influence the behavior and practice of the new generation parents.

[Purpose/Significance] The revitalization of Northeast China in the new era depends on the strong support of scientific and technological talents, and the policies for these talents are essential institutional guarantees for promoting scientific and technological innovation and talent development.This study aims to accurately grasp the framework structure and dynamic characteristics of regional sci-tech talent policies through systematic quantitative analysis, providing decision-making references for deepening the supply-side reform of policies. [Method/Process] Taking the sci-tech talent policy texts of Heilongjiang, Jilin, and Liaoning provinces as research objects, this study employed the BERTopic model to conduct topic identification, keyword extraction, similarity calculation, etc.On this basis, it carried out longitudinal and horizontal comparisons of policy themes among the three provinces and conducted a comparative analysis with the policies of developed provinces such as Guangdong, Jiangsu, Zhejiang, and Shandong. [Result/Conclusion] The sci-tech talent policies of the three Northeast provinces have formed a system with talent introduction, cultivation, utilization, evaluation, incentives, and services as the main lines.However, compared with developed provinces, there are still deficiencies in policy supply, demand traction, and targeting.Based on this, the study proposes that the three Northeast provinces should enhance the systematicity, precision, and timeliness of talent policies based on regional realities, focus on key issues such as policy supply, demand traction, and regional characteristics, and continue to make efforts in the integration, optimization, and innovative development of talent policies.The reform of talent policies in the new era should lead and guarantee the comprehensive revitalization and high-quality development of Northeast China.

[Purpose/Significance] As China's data element market transitions from a disorderly and spontaneous exploration stage to an orderly and standardized formal exploration stage, data security issues have become particularly prominent and have risen to the national strategic level.Exploring the synergy between China's data security policies and scientific research can provide important reference and guidance for promoting scientific research on data security and improving China's data security policies. [Method/Process] This article took 546 policies and 2446 research papers in the field of data security in China as samples, combined with the NMF topic model and Word2vec model, to identify the topics of policy texts and research papers, and explored the evolution and collaborative between China's data security policies and research topics through similarity calculation methods. [Results/Conclusion] China's data security policies and research topics exhibit a synergistic and evolving relationship, and there is a clear trend of collaborative research driven policies in data elements and cross-border data flow topics.

[Purpose/Significance] Based on the five-layer model of user experience, the paper analyzes the influencing factors of the public data open platform of user experience, in order to help the platform improve its construction and realize the upgrade of user experience. [Methods/Processes] Based on the five-layer model of user experience, the paper analyzed the factors, designed hypotheses and constructed models, collected information by using questionnaires, and tested paths, verified hypotheses, analyzed the necessity of the data by using the SEM model and the NCA method. [Result/Conclusions] Among the five-layer of user experience, content requirements, interaction design, interface design and visual performance all have sufficiently significant influence on user experience; in terms of necessity, they are slightly different, and according to the bottleneck level analysis, the degree of necessity is from high to low, which is the content requirements, visual performance, interface design and user requirements, respectively.

[Purpose/Significance] Aiming at health management scenarios, taking real-world individual health and medical data as the research object, we construct a multi-dimensional individual health portrait conceptual model to improve the practicality of individual health portraits. [Method/Process] Based on the review of existing research on individual health portraits, aiming at health management application scenarios, by analyzing real-world individual and group health data, a label system for multi-dimensional health portraits that conformed to real-world data conditions was proposed, and a conceptual model of health portraits including four dimensions: demographic characteristics, health literacy, behavioral habits, and health status was constructed.A health portrait was established for 500000 patients with fatty liver disease in the UK biobank, and a predictive study was conducted based on the health portrait. [Result/Conclusion] A four-dimensional health portrait is constructed based on real-world data.The multiple labels included in the portrait cover the patient's basic indicators, objective indicators and controllable behaviors, reflecting the individual's health status.Through accurate health status identification and long-term outcome assessment, the ROC curves of three models at different time points from single dimension to multi-dimensional were demonstrated.The results showed that with the gradual inclusion of information from the four dimensions, the AUC value gradually increased from 0.58 to 0.64, verifying the effectiveness of multi-dimensional health portraits under the"4P"model in predicting long-term health outcomes, and proving that individual health portraits can help doctors and individuals better understand their health status and promote the implementation of precision health management.

[Purpose/Significance] Public data authorization operation is an important means to promote data transaction circulation and explore data value.From the perspective of policy tools, entering into public data authorization operation policies can help explore the attention allocation of existing policies and provide reference for the future introduction of public data authorization operation policies or documents by the country or other provinces and cities. [Method/Process] Public data authorization operation is an important means to promote data transaction circulation and explore data value.From the perspective of policy tools, entering into public data authorization operation policies can help explore the attention allocation of existing policies and provide reference for the future introduction of public data authorization operation policies or documents by the country or other provinces and cities. [Result/Conclusion] Currently, the operation of public data authorization is still in the exploratory stage, both in theory and practice.After analyzing policy samples, it was found that there are imbalances in the proportion of supply oriented policy tools, abuse of environmental policy tools, and urgent need to expand demand oriented policy tools in the use of policy tools.It is still necessary to coordinate the proportion of supply oriented policy tools Strengthen the balance of environmental policy tools and expand and improve demand based policy tools to optimize the policy system of public data authorization and operation in China.

[Purpose/Significance] The rapid development of generative artificial intelligence (GAI)has brought about revolutionary changes in the field of information retrieval. This paper aims to analyze the learning-related search of users in the GAI environment, and to explore the influence of cognitive styles and task types. [Method/Process] This paper employed user experiments and data analysis methods, utilizing the classification of field-dependence and field-independence cognitive styles. Two types of search tasks, comprehension-oriented and analytical evaluation-oriented were designed to collect data on users' search behaviors and learning outcomes. The data were analyzed using analysis of variance (ANOVA) to test for significant differences. [Result/Conclusion] In the environment of GAI, cognitive styles influence the sources of users' search query construction, the duration of reading generated results, search satisfaction, and perceived knowledge gain. Meanwhile, task types affect the length of search queries, the time spent on constructing search queries, and perceived knowledge gain.

[Purpose/Significance] The generative artificial intelligence technology has triggered the copyright infringement risk during the generative AI data training stage, and infringement litigation cases around the world have emerged. It is of great significance to propose regulatory and compliance measures to deal with the copyright infringement risk of generative AI data training in China, to balance the interests of AI industry and traditional content creation industry, and promote the sustainable development of GenAI technology. [Method/Process] Through the method of literature, comparison and empirical analysis, this paper revealed the regulatory systems of developed countries (areas). On the basis of comparing and learning from the regulatory experience of developed countries, this paper gave the countermeasures in combination with our national conditions. [Result/Conclusion] The study found that China is at the rapid stage of generative AI development. Chinese government should introduce adaptable administrative regulatory principles. Meanwhile, China should incorporate a flexible "fair use" system that is applicable for GenAI data training into the current copyright legal system. At the same time, the industry can also develop a Creative Commons License scheme applicable to GenAI data training as a cost saving compliance measure.

[Purpose/Significance] Trusted data spaces provide critical support for data circulation and utilization.This paper aims to explore the construction principles and development paths of trusted data spaces that align with China's national conditions, providing development momentum for national integrated data element market. [Method/Process] This paper reviewed the research status and practical progress of data spaces through a literature review and case examples.It analyzed, from multiple dimensions, the methods and approaches for addressing challenges in data circulation and utilization through trusted data spaces.Based on these analyses, it systematically discussed construction principles and development paths of trusted data spaces. [Result/Conclusion] This paper proposes BASIC construction principles of trusted data spaces, including balance, accountability, safe, interoperability and controllable, and explores the development paths of trusted data spaces in China from the perspectives of strategic layout, technologies, standards and regulations, innovation ecosystem, operation and supervision, and international exchanges.

[Purpose/Significance] The construction of the ethical order of scientific data sharing aims to strengthen the legitimacy and rationality of the sharing participants' behavior and normalize the sharing process and subjects' relationships.Scientific data sharing is a new type of data empowerment field, leading to the enhancement of the risk and uncertainty of scientific data sharing.Therefore, the construction of the ethical order of scientific data sharing is urgent in order to avoid the ethical disorder of scientific data sharing and data reuse. [Method/Process] On the basis of interpreting the connotation and attributes of the ethical order of scientific data sharing, the actual basis and the necessary requirements for the construction of the ethical order of scientific data sharing were demonstrated, and the construction approach of the ethical order of scientific data sharing was systematically discussed. [Result/Conclusion] The construction of the ethical order of scientific data sharing needs to follow the basic value criteria of idea fairness, process fairness and result justice, guarantee the effectiveness with institutional contract, ensure the enforceability with incentive mechanism, and realize the controllability with the logic of mutually beneficial symbiosis governance on the platform.

[Purpose/Significance] College students' innovation and entrepreneurship team is a new force in China's "mass entrepreneurship and innovation" policy. In recent years, the interdisciplinarity feature of team members has become increasingly prominent. Exploring the influencing factors of interdisciplinary knowledge integration effect can help clarify the improvement path of integration effect, and improve team innovation performance. [Method/Process] According to Wuli-Shili-Renli (WSR) system method ology and literature research, the study extracted the factors that may affect the interdisciplinary knowledge integration effect of college students' innovation and entrepreneurship teams from three aspects, namely, knowledge integration object, process and subject. Then it collected 343 valid data through questionnaire survey, and conducted empirical analysis of influencing factor path and antecedent configuration through structural equation model and fuzzy set qualitative comparative analysis. [Result/Conclusion] Tacit knowledge, interdisciplinary communication intensity, interdisciplinary task interdependence, opinion leader coordination, epistemic stability, epistemic adaptability, emotional trust, intrinsic motivation are significant influencing factors. There are two antecedent configurations that affect the integration of interdisciplinary knowledge, namely, internal drive type and interdisciplinary value co-creation type. And the explanatory power of interdisciplinary value co-creation type is much greater than that of internal driven type.

[Purpose/Significance] From the perspective of risk communication, the identification of the constituent elements of the emergency convergence media information ecosystem, the causal sequence and criticality of the elements are helpful to optimize the system in an orderly and hierarchical manner, and help the emergency response work. [Method/Process] This paper discussed the structural framework of the emergency convergence media information ecosystem, identified its constituent elements, calculated the "four degrees" of each component by using the Fuzzy Set Theory—DEMATEL research method, discussed the causal order and criticality of the constituent elements of the emergency convergence media information ecosystem, and conducted cluster analysis on this basis. [Result/Conclusion] The study identifies 17 cause elements and 21 effect elements among the 38 constituent elements, and 14 key elements among the constituent elements, and the cluster analysis divided the constituent elements into six levels. The research results provide a reference for the orderly and hierarchical optimization of the emergency convergence media information ecosystem.

[Purpose/Significance] Theory is an essential component in the construction and development of the discipline of information science. Organization and Analysis of theories not only help understand the origins and developmental trajectories of the discipline but also predict the development of emerging technologies. Efficient and accurate identification of theoretical entities plays a crucial role in deepening theoretical research. [Method/Process] This paper proposed an information science theory extraction algorithm that collaborates between large and small language models, including modules for enhanced word embedding vectors, sample difficulty assessment, and a theoretical identification model. Initially, the paper used large language models to pre-identify theoretical entities. These pre-identified entities, combined with the original word embeddings, formed the enhanced word embeddings. The training process of domain-specific small models was optimized through these enhanced word embedding vectors. Additionally, the paper used large language models to assess the difficulty of samples and adjusts training strategies accordingly to improve model performance. The proposed algorithm fully integrated the large language models' powerful semantic understanding capabilities and the professionalism of domain-specific small models. [Result/Conclusion] Experiments conducted on a dataset for the extraction of theoretical entities in information science show that the algorithm proposed in this paper effectively improves the performance of theoretical entity extraction, achieving the best results in the metrics of precision, recall, and F1 score.

[Purpose/Significance] The sutdy aims to systematically examine and analyze the current situation, hotspots and frontiers of research on conflicting health information abroad, so as to fully grasp the development of this field and provide useful reference and support for future research directions. [Method/Process] Research literature on conflicting health information was retrieved from two foreign language databases, Web of Science and Elsevier ScienceDirect, and the VOSviewer visualization tool was used to analyze the publication trend, research hotspots and frontiers of the literature, and the analysis results were explained in detail. [Result/Conclusion] Research on conflicting health information abroad is in a stage of rapid development.Research hotspots include: causes and sources of conflicting health information, the impact of conflicting health information on public health cognition and behavior, public health decision-making under conflicting health information and conflicting health information coping and governance.In addition, research fronts cover conflicting health information from the perspective of uncertainty, the carryover effect of conflicting health information, and interdisciplinary theoretical research on conflicting health information.

[Purpose/Significance] Applying virtual digital humans for teaching in educational environments can lead to more efficient online learning for users.This study aims to investigate the impact of virtual digital human characteristics on the effectiveness of users' online learning, providing insights for the design of online instructional videos and the optimization of teaching strategies to enhance learner efficiency. [Method/Process] Based on the theory of parasocial interaction, the study designed instructional video materials featuring virtual digital humans with VTube Studio software, which explored the situation of virtual teachers teaching in online learning environments.Users were recruited to watch the instructional video, and their subjective perceptions were measured. [Result/Conclusion] The features of attractiveness and anthropomorphism of virtual digital humans have a positive impact on online learning performance through a chain-mediated effect of users' attitudes and learning satisfaction with the virtual humans.Additionally, a masking effect exists between the anthropomorphism and learning performance mediation pathway.Parasocial interaction has a positive impact on learning satisfaction, but affects learning performance negatively.

[Purpose/Significance] Intelligent services have become an important direction for the transformation and development of university libraries. Natural language processing technologies empower the intellectualization of university library services, reconstructing service models and processes, and helping improve the overall service levels of university libraries. Named entity recognition is an important task in natural language processing, its impacts and significance on the intellectualization of library services can effectively identify entities such as people, locations, organizations, resource utilization, service features, and cultural promotion in library information, providing support for knowledge organization, information retrieval, etc. [Method/Process] This study analyzed the application prospects of named entity recognition technology in the intelligent service systems of university libraries. By constructing a high-quality library and information science corpus, it provided high-quality training data to meet the specific entity recognition needs within the field, enhancing accuracy and adaptability, and laying the foundation for optimizing library intelligent service systems. An ALBERT-BiLSTM-CRF model based on deep learning was adopted to verify the effects of named entity recognition tasks. Case studies on service recommendations and knowledge graphs in university libraries were performed and compared with existing mainstream large language models at home and abroad. [Result/Conclusion] The results show that the proposed method effectively improves the performance of named entity recognition in the university library information field, which is conducive to the promotion and application of intellectualized library services, while also reducing resource waste and training costs. In addition, this paper explores the possibility of LibraryGPT, a large language model serving the library field, in order to provide references and inspiration for the promotion and development of smart services in university libraries in the future.

[Purpose/Significance] The change of information dissemination and communication methods and the popularity of mobile terminal equipment have brought problems such as overload and stress to personal information management, triggering personal information avoidance behaviors.Investigating the mechanisms through which information overload and system feature overload influence personal information avoidance behavior is crucial for comprehending the occurrence process and triggers behind such behavior.Additionally, understanding these mechanisms can aid in optimizing the user experience with information recommendation services and information management tools. [Method/Process] Adopting a mixed research methodology, this study initially analyzed the key factors influencing personal information avoidance behavior using grounded theory.This process facilitated the construction of a theoretical model outlining the stages leading to the manifestation of personal information avoidance behavior.Subsequently, the study applied the theoretical framework of stressor-strain-outcome to empirically validate the pathways through which various factors influence personal information avoidance behavior in a quantitative research phase. [Result/Conclusion] Information overload and system feature overload positively affect emotional stress, and then lead to personal information avoidance behavior, resilience negatively regulates the relationship between system function overload and emotional stress; information literacy negatively regulates the relationship between information overload and emotional stress.The mixed approach in this study provides a new perspective for understanding the formation mechanism of personal information avoidance behavior, and provides insights for the optimization and improvement of personal information management practice, information recommendation services and information management tools.

[Purpose/Significance] Scholars mostly focused on pursuing the cutting-edge technology of medical intelligence Q&A, with less exploration and research on basic theories, and the two have not been integrated and developed. [Method/Process] On the basis of distinguishing relevant concepts, this study first elaborated on the connotation and characteristics of wisdom Q&A services in the field of online healthcare.Then, it deeply analyzed the connection between knowledge graphs and large language models, as well as the complementary integration ideas of the two in the field of online healthcare wisdom Q&A.Finally, it proposed a framework of online medical health wisdom Q&A services driven by knowledge graphs and large language models. [Result/Conclusion] The article integrates the theoretical characteristics of medical wisdom Q&A services throughout the entire process of wisdom Q&A services, and innovatively proposes that its wisdom Q&A services should include three parts: the construction of medical knowledge graphs driven by large language models, the training of medical large models enhanced by knowledge graphs, and the process of wisdom Q&A services driven by knowledge graphs and large language models.This study achieved a deep integration of theory and technology, and the research results can be used for practical work in subsequent medical wisdom Q&A services.

[Purpose/Significance] Artificial Intelligence (AI)technology has produced algorithmic alienation, innovation, and development.This study takes the alienation phenomenon brought by algorithmic progress as the entry point, introduces the concept of ambivalent attitudes, and studies the mechanism of the formation of academic users' willingness to use Artificial Intelligence Generated Content (AIGC)technology to provide reference and ideas for facilitating the rational use of AIGC technology by academic users, improving the function of platforms by technology service providers, and algorithmic governance by relevant departments. [Methodology/Process] Based on the ABC attitude model and self-regulation theory, the paper constructed a theoretical model of the influence of algorithm alienation on the use of AIGC technology by academic users from the perspectives of algorithm appreciation and algorithm aversion and empirically analyzed 425 questionnaire data by using Structural Equation Modeling (SEM)and Fuzzy Set Qualitative Comparative Analysis (fsQCA)methods. [Findings/Conclusions] SEM results confirmed that ambivalent attitudes significantly negatively affect academic users' willingness to use AIGC.Algorithm appreciation(information quality, functional quality)negatively affects ambivalent attitudes, algorithm aversion(information alienation, governance lag)positively affects ambivalent attitudes, and ambivalent attitudes mediate between algorithm appreciation, algorithm aversion, and willingness to use.Meanwhile, algorithmic literacy and social support mediate ambivalent attitudes and willingness to use AIGC technology.fsQCA results further show that quality-oriented(S1), self-efficacy(S2), and group-driven(S3)form a high willingness to use, whereas risk-averse(NS1)and norm-deficient(NS2)trigger a non-high willingness to use.

[Purpose/Significance] Transferring from search engine search to conversational search has become the trend of users' information search, exploring the influencing factors of users' search transfer behaviors, constructing a comprehensive behavioral transfer analysis framework, and improving the success rate of users' information search transfer behaviors, so as to provide theoretical foundations for optimization of information retrieval systems and conversational search platforms. [Method/Process] Based on the capability, opportunity, motivation-behaviour (COM-B)model, the paper constructed a model of factors influencing users' information search transfer behaviour, used structural equation modelling to analyse the data of 413 cross-sectional questionnaires, and discussed the barriers and facilitators influencing information search transfer behaviour. [Result/Conclusion] Mental ability versus physical ability, physical opportunity versus social opportunity, autonomous motivation versus reflective motivation are positive factors influencing information-seeking transfer behaviours, while insufficient policy support and availability of dialogical search systems are impediments to users' information-seeking transfer, while ability and opportunity can positively influence information-seeking transfer motivation.