[Purpose/Significance] Exploring issues related to the construction of the academic system of the information resources management discipline is an important task to promote the true integration of secondary disciplines such as library science, information science and archival science, and to promote the innovation and long-term development of the information resources management discipline under the new situation. [Method/Process] From the perspective of the concept and composition of the academic system, this article first discussed the connotation and extension of the academic system of information resource management with Chinese characteristics, the constituent elements, and the construction path, and then proposed"DIKW resource management"as the core concept of information resource management discipline and justified its rationality.After that, the emerging academic propositions and basic assumptions of the three secondary disciplines of library science, information science, and archives science were used as the medium to establish interdisciplinary connections around"digital intelligence chain resource management". [Results/Conclusions] Based on the core concept of'DIKW resource management', this article discusses the importance and inevitability of theoretical innovation and reconstruction of the basic theoretical system of the information resource management discipline, and takes archives research as an example to explain the perspective of'DIKW resource management'The innovation of archives research in the new era.

[Purpose/Significance] Analyzing the key factors influencing the formation of "information epidemic"in public health emergencies, which is helpful to solve the problems related to information in future public health emergencies. [Method/Process] Based on the information ecology theory and information niche theory, the four dimensions of"information epidemic"generation factors, were found out, using fuzzy set theory based on dematel method to identify the key factors. [Results/Conclusions] 12 outbreak of"infodemic"key influence factors, such as continuous evolution of epidemic public opinion, and untimely release of government information are identified, and information content publicity and awakening of collective memory of similar events are the unique factors for the generation of"information epidemic", to provide theoretical and practical guidance for the response of"information epidemic"of public health emergencies.

[Purpose/Significance] The study aims to deeply understand the impact of social capital on knowledge social endorsement, and expand research on users' relationships and knowledge social endorsement in knowledge Q & A communities. [Method/Process] This paper constructed a cooperative relationship network of knowledge adopters in a knowledge Q & A community, and explored the internal connections between the knowledge adopters' social capital, social relationship network, and knowledge social endorsement through empirical analysis. [Result/Conclusion]The trust relationship capital of knowledge adopters would have a negative impact on knowledge social endorsement, reciprocity and identification relationship capital, and cognitive capital would have a positive impact on knowledge social endorsement.Cluster coefficient and structural hole indicators have a negative impact on knowledge social endorsement.In addition, the impact of question heat and knowledge popularity would have a positive impact on knowledge social endorsement.

[Purpose/Significance] In the information age, social comparison is gradually penetrating from real life to all aspects of social media user behavior.How to affect users' consumption has become an important issue to be explored in social media enterprises marketing and management. [Method/Process] The study integrated upward social comparisons with downward social comparisons in a framework, adopted the experimental combining the between-groups and within-groups design, and explored the influence of social comparison on user social consumption layer by layer in three experiments. [Result/Conclusion]On the one hand, it is found that upward social comparison is positively associated with conspicuous consumption and herd consumption, while inferiority complex mediates the effect of upward social comparison on conspicuous consumption and herd consumption, and counterfactual thinking mediates the effect of upward social comparison and inferiority complex; on the other hand, downward social comparison is positively associated with conspicuous consumption and scarcity consumption, counterfactual thinking and happiness have a masking effect between downward social comparison and consumption.

[Purpose/Significance] Taking TikTok short video as an example, the study deconstructs the whole process of intermittent dropout behavior of its users, studies the factors affecting their behavior and behavior patterns, explores the process, inner mechanism and occurrence pattern of intermittent dropout behavior of weakly related social media users, and provides optimization strategies for the construction of related information platforms. [Method/Process] The study used the rational behavior theory model and combining with related literature to construct the model; adopted the mobile empirical sampling method to obtain the original data of intermittent intermittent dropout behavior of TikTok users; used PLS-SEM to analyze the data, verified the model, and revealed the influencing factors according to the results. [Result/Conclusion] The intermittent dropout behavior of users is expressed as"dropout-adopt again-(dropout-adopt again-……)dropout"which is a cyclic process.Among them, perceived cost, system quality, and group norms stimulate users to generate intermittent dropout intention, and then generate intermittent dropout behavior; social needs, perceived pleasantness, switching barriers, and group norms stimulate users to generate re-adoption intention, and then generate re-adoption behavior.

[Purpose/Significance] Video is widely used in various network applications.It is of great academic and commercial value to study the influencing factors of users' continuous use behavior of bullet screen video website. [Method/Process] Video feature data and user behavior data of Bilibili website were used to construct multiple linear regression and SHAP interpretable model based on machine learning, and explore the influencing factors of video users' continuous use behavior and the importance, positive and negative of its influencing polarity from three dimensions of content perceived value, emotional perceived value and social perceived value. [Result/Conclusion] The study finds that the number of likes represents the user's content perceived value of the video mostly, and the content perceived value has the highest impact on the user's continuous use behavior; among the up hosts(video producers)with a medium to high number of fans, emotional perceived value has a higher impact on users' continuous use behavior, while among the up hosts with the highest number of fans, social perceived value has a higher impact on users' continuous use behavior.

[Purpose/Significance] The study aims to explore the computational model of diagnostic and therapeutic norms under the guidance of computable biomedical knowledge, in order to drive the "data-knowledge-practice-data" cycle progression, and promote the collaborative development of decision-making in all links of the clinical diagnosis and treatment process. [Method/Process] The research aimed to clarify the necessity and application value of knowledge computerization of diagnostic and therapeutic norms through literature research.On the basis of clarifying the concept and connotation of diagnostic and treatment norms, summarizing the data sources and data characteristics of diagnostic and treatment norms, and refining the knowledge computable features of diagnostic and treatment norms, this research followed the core idea of computable biomedical knowledge and the connotation of DIKW hierarchical model, constructed a knowledge computerization model of diagnostic and therapeutic norms, and explored its implementation path. [Result/Conclusion] Building a "1-336" model cube for diagnostic and therapeutic norms knowledge computerization, its includes one core goal, three knowledge levels, three implementation sub-paths, and six key links, so as to provide theoretical support and methodological reference and basis for knowledge computing research in various fields.

[Purpose/Significance] Currently, artificial intelligence technology is unleashing a revolutionary transformation between productivity and production relations around the world.Artificial intelligence-generated content(AIGC)is reshaping the knowledge ecosystem and digital technology environment we live in.Therefore, exploring how AIGC can promote the development of scientific and technological information services in China is of great significance under the trend of intelligent scientific and technological information services. [Method/Process] This paper summarized the technical core and advantages of AIGC, combined the problems and needs faced by China's scientific and technological information services in the era of Intelligence 3.0, discussed the technical application path of AIGC in scientific and technological information services, and attempted to construct an intelligent service framework for scientific and technological information driven by AIGC technology.This paper proposed a scientific and technological information intelligent service framework consisting of a support layer, an intelligent application layer, a platform service layer, and an output layer. [Result/Conclusion] Through the application of new technologies, the intelligent level of China's scientific and technological information services can be promoted and the innovation and development of scientific and technological information services can be promoted.

[Purpose/Significance] The study aims to provide theoretical support for the promotion of open government data, explore the influencing factors of the development process and implementation quality of open government data and analyze the interaction between various factors and subjects. [Method/Process] Based on the target theme, the study used meta-synthesis methods to conduct explanatory coding and comprehensive induction for the selected literatures.Subsequently, conducted the framework for influencing factors of open government data, and analyzed the functional relationships between various dimensions and categories within the framework. [Result/Conclusion] A novel GTEV model successfully establishes and it consists of four dimensions: Government organization, Technical support, internal and external Environment, and Value realization.This model describes the process of open government data as a comprehensive dynamic system with the interaction of multi-subjects and multi-factors, which provides an important reference for the subsequent research on open government data.

[Purpose/Significance] Through quantitative evaluation and comparative analysis of scientific data management policies between China and the United States, this article provides a reference for the improvement of China's scientific data management policy system. [Method/Process] The study took the scientific data management policies of China and the United States as the research object, using text mining and content analysis, an evaluation constructed index system containing 9 primary variables and a PMC-AE index model to comprehensively evaluate and quantitatively analyze 14 scientific data management policies of the two countries. [Result/Conclusion] The overall level of China's scientific data management policy is lower than that of the United States, and the PMC-AE score of scientific data policy increases with the increase of effectiveness level and decreases with the increase of specificity intensity.China should fill in policy gaps, improve policy construction at the meso and micro levels, accelerate the implementation of scientific data strategies, improve evaluation and assessment mechanisms, and strengthen the construction of policy guarantee systems.

[Purpose/Significance] With the advent of the digital intelligence era and the continuous development of higher education evaluation in China, the public's demand for higher education evaluation information and services changes significantly, and needs more effective higher education evaluation information services urgently.Designing an intelligent information service model of higher education evaluation for the public provides new ideas for innovating the practice of higher education evaluation in the era of digital intelligence, and provide reference for the future all-round intelligent service of higher education evaluation information. [Method/Process] The study guided the design of the overall intelligent information service model framework by using data-driven and intelligent information processing connotations, theories and methods, and justified the evaluation of the overall model through the entropy-based fuzzy comprehensive evaluation method. [Results/Conclusions] The study constructs a model framework of higher education evaluation information demand mining, demand-resource mapping and overall intelligent information service for the public, proposes a specific intelligent service approach for higher education evaluation information, and demonstrates the effectiveness of the model.

[Propose/Significance] As an emerging type of citation evaluation index, the standardized evaluation index considers the influences of multiple factors on the paper citations, and therefore exhibits the remarkable advantage in the evaluation of academic achievements.It is of great significance for the evaluation of academic papers to investigate the correlations among different standardized evaluation indices. [Method/Process] In this paper, papers in ten academic areas from the InCites database in 2018—2022 were selected as the research samples, and the correlation analyses for relative citation ratio(RCR), category normalized citation impact(CNCI)and journal normalized citation impact(JNCI)of these papers.The study further made comparative analyses on the RCR and CNCI of papers from different countries and research institutes was further made. [Result/Conclusion] The results show that in ten academic areas, there exist a positive correlation among three indices.For most of areas, both RCR vs CNCI and CNCI vs JNCI have the strong positive correlations, while the RCR vs JNCI has a relatively weak correlation.For different academic areas, the average RCR and CNCI of country or research institution can reflect its academic level and academic influence.The current study to a certain extent revealed the differences and correlations among RCR, CNCI and JNCI in the evaluation of the academic influence of papers in different academic areas.

[Purpose/Significance] The mining, utilization, and evaluation of knowledge entities in scientific literature are significant to knowledge discovery, knowledge network construction and potential relationship exploration.With the development and application of machine learning, deep learning and large language models, tremendous changes take place comparing with the earliest knowledge entity extraction technology based on manual annotation.In addition, in recent years, scholars make some explorations on the evaluation of knowledge entities in scientific literature and made great progress. [Method/Process] On the basis of literature investigation, this paper reviewed and compared the advantages and disadvantages of manual annotation-based methods, rule-based methods, traditional machine learning, deep learning, and large language models in knowledge entity extraction, and listed relevant data sets, software and tools, and relevant professional conferences.This paper summarized the latest research progress in the evaluation of knowledge entities from five aspects: mention frequency, altmetrics and its influencing factors, entity co-occurrence network and entity diffusion/citation network, peer review, novelty, and clinical translation progress of papers based on knowledge entities. [Results/Conclusions] In view of the existing problems, it is suggested that in the specific knowledge entity extraction task, the selection of extraction method should weigh many factors, and then select one or more models to complete the entity extraction task.In terms of knowledge entity evaluation, the study should pay attention to the diversification, reliability, validity, systematization, and standardization of indicators, pay attention to the empirical analysis of influencing factors of evaluation indicators, correlation, and causality among indicators, build a paper evaluation indicator system based on knowledge entities, and empower future science and technology evaluation and application from a fine-grained and intelligent perspective.

[Purpose/Significance] This paper summarizes the advantages and disadvantages of different methods, summarizes the problems in the existing research and provides reference for the research of emerging topic identification. [Method/Process] Firstly, this paper differentiated and analyzed the emerging topic and the related concepts; secondly, according to the process of emerging topic identification, combed and analyzed the relevant literature sets from three aspects: the selection of data sources and analysis objects, the method of identifying topics, and the attributes and indicators used to screen for emerging themes; finally, put forward the limitations and shortcomings of the existing research and made prospects for future development. [Result/Conclusion] After two decades of development, emerging topic identification research forms a more standardized research process and rich research methods, but there are still certain shortcomings.At the theoretical level, the definition of emerging topics is still unclear; in terms of data set construction, the selection of data sources and fusion methods need to be improved; in the aspect of topic recognition, the research methods have a strong time lag, and insufficient semantic attention and interpretation; in terms of screening indicators, the evaluation system is not objective and complete.In the future, more in-depth research on relevant theories and research methods are needed.