[Purpose/significance]The unique form and systematic characteristics of great power competition, such as system-establishment and whole of society confrontation, multi-domain and multi-depth high-tech containment and counter-containment, and multi-means and multi-element mixed deterrence, determine that national scientific and technological intelligence must have considerable systemic capabilities to match and follow up. [Method/process]This article focuses on scientific and technological intelligence institutions within the traditional system, defines the connotation of national scientific and technological intelligence system capabilities, constructs a six-dimensional capability cognition model of "institutional improvement capability-system coordination capability-resource guarantee capability-technological innovation capability-intelligence shaping capability-safe operation capability", and expounds its main contents. [Result/conclusion]Based on the six-dimensional capability cognition model, this article proposes the main tasks for the development of national scientific and technological intelligence system capabilities, with a view to providing reference for achieving optimal overall emergence of the national scientific and technological intelligence system.

[Purpose/significance]The security intelligence process is the fundamental path for intelligence to support security governance and decision-making. The incompleteness and even deceptive nature of the information relied upon in security intelligence activities, as well as the concealment and adversarial nature of security issues, determine significant differences in the scientific perspective and methodology of constructing security intelligence processes compared to other intelligence processes. [Method/process]Starting from the analysis of existing problems in the security intelligence process and optimization suggestions, this article constructs a security intelligence process model based on the conceptual model of the intelligence process, based on the information chain theory. [Result/conclusion]The constructed security intelligence process model emphasizes intelligence requirement management based on security event systems, strategic intelligence research oriented towards conceptualization of security event systems, and operational mechanisms such as the integration of intelligence business flow and security information flow. In addition, this article provides strategies for identifying intelligence requirements, evaluating the reliability of information sources, iterating and upgrading information collection, understanding the meaning of information, protecting intelligence activities, and identifying proactive defense and opportunity creation, among other key questions of the security intelligence process.

[Purpose/significance]Starting from the related concepts of disciplinary topic evolution, this study comprehensively examines the forms and methods of disciplinary topic evolution. It identifies problems with existing concepts and shortcomings in current methods, and suggests directions for improvement, providing a reference for future research in this area. [Method/process]Using a systematic review method, the literature on disciplinary topic evolution from the CNKI and Web of Science, as well as other academic platforms, was analyzed. The study defines related concepts, summarizes the forms of disciplinary topic evolution, and systematically reviews the current state of research on methods for disciplinary topic evolution. It analyzes existing methods from different perspectives： word frequency-based methods, co-word-based methods, citation-based methods, and topic model-based methods, summarizing their respective advantages and disadvantages. [Result/conclusion]This study defines the concept of disciplinary topic evolution, clarifies the forms of disciplinary topic evolution, and summarizes the gaps in existing research, such as the unclear definition of the concept, non-standard evolution forms, single data sources and the limited diversity of analytical methods. Finally, it proposes future directions, including clarifying the connotation and extension of disciplinary topic evolution, standardizing its forms, utilizing multi-source data as data sources, and actively integrating different methods for topic evolution analysis.

[Purpose/significance]Clarifying the influencing factors of young scholars' willingness to use AIGC and its path of action,then making effective enhancement strategies,would help to further expand the application of AIGC in academic writing. [Method/process]This paper combs through the studies on AIGC information behavior, and identifys TOE(Technology-Organization-Envifonment，TOE) theory and research life cycle theory as the base theory. Semi-structured interviews were conducted for procedural grounded theory coding. Then, a questionnaire survey and qualitative comparative analysis using fuzzy sets were conducted to obtain the influencing factors grouping path. [Result/conclusion]Five factors, induding content quality, system quality, perceived risk, expectation confirmation, and group norms, together constitute an influential model of willingness to use AIGC in young scholars' academic writing. The group norms analysis produces three paths of high-level willingness to use: system-dominant, expectation-group double-dominant, and content-expectation double-dominant paths. Strategies are proposed to improve the willingness to use AIGC in young scholars' academic paper writing, including improving the quality of content and optimizing the platform system at the technical level, improving the literacy of AI-use and managing expectations at the individual level, and accelerating the formation of norms and encouraging publicity and guidance at the environmental level.

[Purpose/significance]Analyzing the perceptions of mainstream U.S. think tanks towards the China-U.S. competition in quantum science and technology contributes to examining their thinking frameworks and strategic judgments, providing strategic insights for China to effectively respond to U.S. containment and blockade in this field. [Method/process]By selecting 13 research reports from 8 mainstream U.S. think tanks and utilizing the literature analysis method, this study systematically reviews the multidimensional perceptions of U.S. think tanks on the China-U.S. competition in quantum science and technology, thus revealing the underlying logic behind their perceptions. [Result/conclusion]U.S. think tanks generally advocate for competition with China in quantum science and technology in the name of safeguarding national security. Their perceptions clearly reflect an underlying logic of right-wing political tendencies, techno-nationalism, and national policy orientations. In light of this, China should incorporate elements such as independent innovation, international cooperation, and supply chain security into policy considerations.

[Purpose/significance]This study investigates differences in digital medical-health information privacy preferences by measuring privacy sensitivity across diverse user groups in multiple contextual scenarios, analyzing variations both within user groups (across contexts) and between user groups (within the same context), thereby providing actionable insights for developing context-aware health information protection frameworks in digital healthcare services. [Method/process]A model of users' sensitivity to digital medical health information was constructed based on contextual integrity theory, and an experimental study was conducted using a discrete choice experiment method. The model was verified and analyzed using a binary logistic regression model. [Result/conclusion]The study shows that in the information subject dimension, highly educated users are more willing to pay extra fees to choose platforms with a higher level of privacy protection or the ability to set a higher level of privacy on their own compared to less educated users. Regarding communication principles, users prefer platforms that offer transparent and easily comprehensible privacy policies. In terms of information types, users tend to safeguard their health status information and payment data while being willing to share basic personal information and medical application data to a certain extent in exchange for more convenient healthcare services or health management solutions.

[Purpose/significance]To explore the internal formation mechanism of unplanned irrational online comments is of great significance to promote the governance of cyberspace and the control of user behavior. [Method/process]Based on the dual-system theory, the study constructed a model for the formation mechanism of irrational online comments, and revealed how online disinhibition and the spiral of silence affect individual internal states to stimulate irrational comments through empirical analysis. [Result/conclusion]Research reveals that:compared to mild irrational comments, aggressive irrational comments are more likely to be unplanned behaviors; the cognitive-emotional preoccupation with online comments is the main driving factor for irrational online comments, while the cognitive-behavioral control over online comments plays a partial inhibitory role; online disinhibition intensifies cognitive-emotional preoccupation and weakens cognitive-behavioral control, while the spiral of silence simultaneously strengthens cognitive-emotional preoccupation and cognitive-behavioral control; online disinhibition and the spiral of silence positively affect irrational online comments through the mediating role of cognitive-emotional preoccupation; cognitive-behavioral control serves as a mediating factor in the impact of online disinhibition on aggressive irrational comments.

[Purpose/significance]This study addresses the issue of inadequate perception of entity boundaries in traditional character-level modeling-based named entity recognition models by integrating syntax information containing entity boundary features into the task using a multi-head graph attention network with dense connections. This integration enhances the effectiveness of named entity recognition. [Method/process]This study proposes a Syntax-enhanced Boundary-aware Named Entity Recognition Model (SynBNER), which utilizes BERT for text semantic representation and integrates syntax information using a dense-connected graph attention network. This integration incorporates implicit entity boundary information from syntax information into word representations, thereby enhancing the model's entity boundary perception capability. [Result/conclusion]Empirical studies are conducted on the ACE2005, MSRA, and People's Daily datasets, the F1 scores of the SynBNER model are respectively 86.11%, 96.03%, and 95.81%. The experimental results demonstrate that the method of enhancing entity boundary awareness with syntax information can significantly improve the effectiveness of named entity recognition.

[Purpose/significance]This research constructed a domain knowledge graph and its scenario-oriented application framework for decision support at four levels: the data foundation layer, the key technology layer, the domain knowledge graph construction layer, and the scenario-oriented application layer. This framework aims to provide systematic support for knowledge discovery. [Method/process]Based on the construction of a domain knowledge graph and its scenario-oriented application framework for decision support, this research focuses on the improvement of models and performance evaluation for fine-grained entity and relationship extraction at the discourse level within texts. The optimal model is selected to construct a domain knowledge graph. Taking the field of transformer equipment failure as an example, empirical studies are conducted to realize scenario-oriented applications aimed at decision support. [Result/conclusion]The integrated pipeline knowledge extraction method, which combines the improved BERT-BiLSTM-CRF model and the PURE-RE model, has demonstrated superior comprehensive performance. The knowledge graph constructed for the domain of transformer faults has been verified against the expert knowledge in the "Equipment Standard Defect Knowledge Base", and the search results have passed verification. This effectively assists maintenance personnel in equipment inspection and maintenance, thereby validating the effectiveness and practicality of the framework established in this research. With the support of domain expert knowledge verification, it can effectively empower related fields to conduct decision support.

[Purpose/significance]Under the background of the overall strategic competition between the United States and China, measuring and analyzing the topics and trends of American think tanks’ products on China is conducive to understanding the American perception and policy moves towards China. It holds important heuristic significance for coping with external risks, maintaining national security and strategizing for development. [Method/process]Using the full data of research outputs on China from 11 American think tanks as the research sample, this paper explores the topics and evolutionary trends of American think tanks’ products on China, as well as their correlation with China-US economic and diplomatic interactions, through the Structural Topic Model (STM). [Result/conclusion]American think tanks have shown a high level of attention to China in recent years. Their focus centers on six broad categories encompassing 26 themes, such as international affairs of China, China economy, China technology, China-US relations and so on. Different topics show different temporal evolutionary trends, and they have significant correlations with China-US economic and diplomatic interactions.

[Purpose/significance]Topic evolution analysis can help researchers quickly grasp the research hotspots and development trends of a discipline. However, existing topic models often overlook the semantic functions and structures of texts during topic extraction, making it difficult to reveal the deeper patterns of disciplinary development. This paper proposes an integrated framework for topic evolution analysis that combines the BERTopic model with semantic functions, aiming to enrich and improve the methodological system of topic evolution research. [Method/process]Firstly, the BERTopic model is used to extract topics, obtaining the “Topic-Word” distribution. Next, a discourse parsing tool analyzes abstracts into five semantic function segments, resulting in the “Semantic Function-Word” distribution. Finally, the two distributions are mapped to obtain the “Topic-Semantic Function” distribution. This approach analyzes topics from a semantic function perspective and explores the impact of semantic function distribution on topic evolution. [Result/conclusion]An empirical study in the field of library and information science shows that the semantic function distribution of a topic affects its research popularity. Topics oriented towards “Method” and “Objective” may continue to rise in the future, while topics oriented towards “Background” are relatively mature and may enter a decline phase. The proposed method provides a more granular and accurate analysis of discipline development dynamics, helping the academic community better understand the dynamic changes in research hotspots.

[Purpose/significance]This study aims to identify the expertise domains of medical experts, and evaluates their domain levels to provide a basis for community expert recommendation. [Method/process]This study utilized the improved OneRel model to structure community historical Q&A into entity relation triples. Then used the knowledge graph triples to test the consistency between the medical knowledge in the community Q&A and the domain knowledge, and finally obtained the doctor's domain levels by aggregating in each expertise domain. [Result/conclusion]Using the data example from xywy.com website, 214 doctors in the community were ranked in terms of their average level of expertise domains and their respective reliable domains levels were identified. The study verified that the basic information self-reported by doctors in online health communities, such as their expertise and personal profiles, did not fully correspond to their real competence characteristics. Compared with other medical expert discovery methods, this method can intelligently identify and evaluate doctors' expertise domains, demonstrating objectivity, accuracy, and strong interpretability.

[Purpose/significance]In December 2024, the 7th Chengdu Conference on Scientometrics & Evaluation was held in Chengdu. This article was conducted to summarize the salon on Full-text Bibliometric analysis of the forum, and reveal the research status and development trends of full-text bibliometric from the perspective of knowledge innovation, providing inspiration for future. [Method/process]The article systematically summarizes and analyzes the presentations and discussions from the salon, exploring the theoretical foundation, application scenarios, and discussions of full-text bibliometric from the perspective of knowledge innovation. [Results/conclusion]Full-text Bibliometric can reveal the micro-processes and underlying mechanisms of knowledge innovation, offering new insights and methods for related research. Its applications in technological evolution and industry-academia integration, scientific data warehouse evaluation, policy text analysis and intelligent computing, as well as entity relationship extraction in academic papers, demonstrate its vast potential in promoting academic research, optimizing policy-making, and driving knowledge innovation. However, the integration of full-text bibliometric analysis with large language models, open science, and research integrity presents numerous challenges.

[Purpose/significance]Public security intelligence work has undergone a significant transformation from passive defense to proactive early warning,with corresponding shifts in its core functions. The cultivation of public security intelligence talents rooted in practical combat has evolved alongside the development of intelligence work,necessitating a clear understanding of its historical development and future prospects. [Method/process]By employing a comprehensive approach that integrates literature analysis,data interpretation,and historical examination,this study systematically reviews the evolution of public security intelligence education from the perspectives of practical intelligence work,the overarching public security education system,and the specific aspects of intelligence education.It delves into the transformative characteristics and driving forces of talent cultivation in public security intelligence. [Result/conclusion]The rapid iteration of public security intelligence operations presents multidimensional challenges and opportunities for public security intelligence education.To adapt to this transformation,future education in this field must focus on cultivating talent with a practical orientation,vigorously developing the discipline of public security intelligence,deepening the scope of intelligence technology education,establishing a systematic theoretical framework for intelligence education, and establishing a modern on-the-job training system for public security intelligence.These efforts aim to nurture a workforce capable of leading practical intelligence operations and possessing high levels of professional expertise and innovation capability.

[Purpose/significance]The development of new quality productive forces is a crucial strategic goal for national progress, with local policies serving as important conduits for conveying and implementing national strategies. Researching local policies that promote the development of new quality productive forces is significant for the implementation of the national strategy in different regions and for further policy evaluation. [Method/process]By constructing a theme-tool-effectiveness analysis framework and employing LDA topic model, policy tools, and PMC index model, this study conducts a multidimensional quantitative evaluation of local policy texts related to the development of new quality productive forces. [Result/conclusion]The study finds that the distribution of policy quantity follows the trend of East China > Central China > South China > North China/Southwest China > Northeast China > Northwest China. Policy themes comprehensively reflect the main actions of local governments in promoting new quality productive forces, with East China primarily supporting specialized and innovative small and medium-sized enterprises, while Central China focuses on supporting industrial transformation and upgrading. Across the seven major regions, there is a general tendency to use environmental policy tools more than supply-side and demand-side policy tools. The average PMC index for policy effectiveness is above good, with East China having the highest overall PMC score. However, certain issues merit attention: there are significant differences in the use of policy tools across themes, and there is an imbalance between internal and external use of policy tools. Policy effectiveness is still relatively weak in terms of policy content, policy areas, policy targets, and localization. It is recommended that local strengthen the diversity of policy themes, governments enhance the balance of policy tools and improve the comprehensiveness of policy effectiveness during policy formulation.

[Purpose/significance]Disruptive technology is regarded as a revolutionary force that "changes the rules of the game" and "reshapes the future pattern", and has gradually become a hot and difficult issue in interdisciplinary research. This paper summarizes the literature related to disruptive technologies, clarifies the concepts and characteristics of disruptive technologies, subdivides research topics and directions, summarizes research focuses and looks forward to future development trends, and provides reference for relevant personnel. [Method/process]On the basis of sorting out the latest related research on disruptive technologies, this paper clarifies the research progress of disruptive technologies from three aspects: the concept and characteristics of disruptive technologies, common identification methods, and the evolution and prediction analysis of disruptive technologies, and grasps the research status and development trend of this field. [Result/conclusion]This paper comprehensively summarized the current research status of disruptive technology, and analyzed the existing problems and shortcomings.

[Purpose/significance]The public data authorization and operation policy plays an important guiding role in further guiding and regulating the practice of public data authorization and operation， as well as promoting the development and utilization of public data. Analyzing the existing public data authorization and operation policies can provide important references for the development of public data authorization and operation practices， as well as for policy formulation and improvement. [Method/process]This article selects relevant policies on public data authorization and operation issued by various levels of government in China， and uses the structural topic model to analyze and evaluate the existing policy texts. [Result/conclusion]The research shows that existing public data authorization and operation policies focus on three main themes： data security， data sharing and openness， and operational supervision. Among these， there is more emphasis on the supervision of public data operation platforms， while there is less attention paid to data security and data development. Based on this， the article proposes targeted countermeasures and suggestions， aiming to provide references for the practice of public data authorization and operation and policy formulation.

[Purpose/significance]This paper analyzes the relevant literature in the field of AI for Science （AI4S） in the WoS core database from 2015 to 2024, and sorts out the research status and development trends in this field, aiming to provide forward-looking insights for the application of AI technology in scientific research. [Method/process]This paper combines bibliometric analysis with the BERTopic model to analyze the publication trends, publishing countries, core authors, and topic identification and development trends in the field of AI4S. [Result/conclusion]Through bibliometric analysis, this paper reveals the exponential growth trend of AI4S-related literature, and finds that China ranks first in the number of publications but the number of citations is slightly lower than that of the United States. The study also identifies the core authors and highly cited papers of foreign AI4S research. Through the BERTopic model, 22 topics were identified and summarized into six major research directions. The key application fields include artificial intelligence and educational technology research, medical health and artificial intelligence diagnosis, precision agriculture and climate change, materials chemistry and deep learning, and high-performance lithium battery technology. Some topics such as AI and precision agriculture, AI and mental health, and AI and lithium battery technology have been research hotspots in recent years.

[Purpose/significance]Financial competitive intelligence is a core element in promoting the stable development of new ventures. Based on big data thinking, exploring the construction process and simulation effects of financial competitive intelligence warning mechanisms for new ventures is of great significance for improving their competitiveness and promoting healthy development. [Method/process]The article takes startups as the research object, constructs a financial competitive intelligence early warning mechanism for startups based on big data thinking, and uses system dynamics methods to construct causal relationship diagrams and system flow diagrams, and simulates them using Vensim PLE software. [Result/conclusion]The system dynamics model constructed in the article can well fit the financial competitive intelligence warning process and reveal the positive effects of factors such as the application rate of big data technology, key financial indicators, intelligence analysis methods, internal financial personnel participation rate, and professional audit personnel participation rate on financial competitive intelligence warning. This provides new ideas for new startups to smoothly carry out financial competitive intelligence warning work.

[Purpose/significance]The deep integration of ancient book digitization and large language models is the future development trend. In order to clarify the influence factors and formation mechanisms of dropout behavior among users of domain ancient book large language models, mobilize the willingness of users to use large language models, achieve high-quality user retention, and promote the non-human high-quality development of domain large language models. [Method/process]This study takes users in the field of ancient books as an example, based on resilience theory, and draws on grounded theory research methods to code and deconstruct first-hand data obtained from in-depth interviews with 30 users of ancient book large language models. The focus is on extracting influencing factors and conceptual categories from the perspective of resilience theory, and then constructing a research model on the mechanism of dropout behavior formation among users of ancient book large language models from the perspective of resilience theory. [Result/conclusion]The research results show that resilience factors, psychological resilience, cognitive factors, and situational factors are important factors affecting the dropout behavior of users of the ancient book large language model.Resilience factors include three dimensions:information resilience, technological resilience, and environmental resilience. Psychological resilience mainly goes through three stages: emotional stress, emotional resilience, and cognitive resilience.The research results provide necessary reference for effectively preventing users of ancient language models from dropout and achieving high-quality user retention.