［Purpose/significance］ With the emergence of ChatGPT,algorithm applications increasingly dominate human life,algorithm black box,algorithm manipulation,algorithm collusion,algorithm bias,algorithm discrimination and other risks also follow,these risks seriously affect social stability and even national security.The research and judgment of the global algorithmic risk situation can help to prevent and identify algorithmic risks,and provide Chinese wisdom and ideas for dealing with the global algorithmic risk governance problems.［Method/process］ The article systematically reviews 915 core literature from major domestic and foreign databases,constructs an algorithm risk research framework based on “subject areas research topics governance tools governance measures”,and analyzes the interdisciplinary,complex interweaving,prominent anthropomorphism,and generalized uncertainty characteristics of algorithm risk.［Result/conclusion］ From five aspects:strengthening the research on algorithmic risks in the field of intelligence science,enhancing the interpretability of artificial intelligence algorithms,strengthening research on algorithmic application and service improvement,and strengthening research on global algorithmic risk management and China’s wisdom and vision,this paper looks forward to the challenges of algorithmic risks.

［Purpose/significance］ Open Public Data,as a vital component of public data,is critical for effective utilization.Analyzing the mechanisms for releasing the application value of Open Public Data can enhance its effective use.［Method/process］ Based on the SOR framework,this study treats application scenarios as stimuli and analyzes their connotations and attributes.The paper then identifies the key participants on both the supply and demand sides of Open Public Data,explores their behavioral responses through case studies,and proposes mechanisms and pathways for realizing the value of Open Public Data driven by application scenarios.［Result/conclusion］ The study concludes that the application-scenario-driven value release mechanism of Open Public Data comprises five fundamental aspects,namely:scenario objectives,demands,collaboration,application,and iteration.The pathways for value realization include enhancing data demand management,refining data openness policies,optimizing the development of open data platforms,integrating technological solutions into practice,and establishing mechanisms for feedback and evaluation.

［Purpose/significance］ A behavioral phenomenon of information cocoon retention exists in the context of network stratification.Studying the characteristics and influencing factors of retention behavior can help dig out the reasons for the formation and consolidation of the information cocoon,help social media users to enhance the awareness of “breaking the cocoon”,and provide ideas and strategies for the governance of cyberspace.［Method/process］ Taking Douban group users as samples,this paper first explores the performance characteristics of social media users’ information cocoon retention behavior through in-depth interviews and open coding.Based on the results of qualitative analysis,we construct a model of factors influencing information cocoon lingering behavior,collect questionnaire data to test the hypotheses,and use fsQCA to conduct supplementary analysis from a group perspective.［Result/conclusion］ The study concludes that the performance characteristics of social media users’ information cocoon retention behavior are diverse,and the factors affecting this behavior include system function,circle building,performance expectations,hedonic motivation,usage habits,information homogeneity,and information overload,and the path of causes of social media users’ information cocoon retention behavior is complex.

［Purpose/significance］ Assessing the maturity of scientific research big data governance is crucial,yet the lack of evaluation theory and practice exacerbates issues such as fragmentation,dormancy,and hibernation within this field.This paper endeavors to construct a maturity assessment model for scientific research big data governance through a data ecology perspective and refine the evaluation method.［Method/process］ By leveraging data ecology theory,a data model is proposed,leading to the development of the (maturity model of scientific research big data governance based on data ecology,MM-SRBDG).The MM-SRBDG model comprises 8 core domains,29 capability domains,and 101 process domains,alongside an indicator system.Additionally,a comprehensive evaluation method,E-C-A,is formulated,followed by practical case-based assessment and systematic analysis.［Result/conclusion］ The MM-SRBDG model systematically delineates the constituent dimensions of scientific research big data governance maturity,offering a new perspective for systematic governance in this domain.The constructed indicator system and evaluation matrix exhibit systematic and in-depth characteristics.The E-C-A method,tailored to diverse dimensions,furnishes both theoretical grounding and practical guidance for assessing scientific research big data governance maturity,thereby enhancing governance standards.

［Purpose/significance］ While the development and application of AI technology promotes the change of human society,it also destroys the trust between people and technologyExploring the relationship between algorithmic transparency and userperceived trustworthiness can help break down the algorithmic black box,reshape technological trust,and develop usertrustworthy AI［Method/process］ In this study,50 participants were recruited to carry out eyetracking experiments using WeChat moments as the research platform,combining questionnaires and interviews to explore users’ perceived trustworthiness of personalized recommendation ads under different transparency scenarios,to clarify the trust relationship between people and algorithms,and to propose transparency improvement strategies from the perspective of trust［Result/conclusion］ It is found that users’ perceived trustworthiness is affected by factors such as transparency level,the content and structure of transparency,etcWe should develop reasonable,efficient,accessible and comprehensible algorithmic transparency to improve users’ trust and promote the development of trustworthy AI［Limitations］ This study has a single sample source and research perspective,and the subsequent experiments will be scaled up to explore the differences in perceived trustworthiness of different user groups

［Purpose/significance］ In the era of digital intelligence,with the widespread application of algorithms in intelligence analysis,revealing the current status of algorithm usage in intelligence analysis not only helps scholars in the field of intelligence to grasp academic research hotspots,but also guides more researchers to better use algorithms to solve practical problems in the process of intelligence analysis.［Method/process］ This paper focuses on the literature related to intelligence analysis algorithms in five core journals in the field of information science in the past decade,attempts to sort out the classification of algorithms applied to intelligence analysis in the era of data intelligence,and presents the characteristics of these algorithms from the perspective of algorithm evolution and algorithm application.［Result/conclusion］ From the perspective of evolution,papers on applied algorithms in the field of information science continue to rise in the past decade,and LDA is the most used algorithm in intelligence analysis.Since 2020,BERT algorithm has shown a prominent feature of new evolution.From the application point of view,the applications of online public opinion and patent analysis under emergencies show a trend of continuous refinement and inheritance evolution;Applications such as libraries,library information,e-commerce,and logistics information are gradually declining,replaced by digital humanities,smart libraries,and disruptive technologies.

［Purpose/significance］ In the wave of digitization,the digital disadvantaged groups who cannot effectively access digital technology due to subjective and objective reasons often take the action of digital rejection or resistance.It is of great significance to explore the key influencing factors of digital rejection of this group and analyze the current situation and optimization path of digital inclusion policy tools.［Method/process］ Based on the perspective of theory-policy coordination degree,this study adopts meta-ethnography and DEMATEL method to identify the key influencing factors of digital exclusion of the digital disadvantaged groups,using the theory of personal information world.Then content analysis of the current digital inclusion policy focus is carried out,and finally policy optimization paths are proposed.［Result/conclusion］ Nine key factors are identified,including digital literacy,function-requirement matching degree,information infrastructure and volunteer service resources.The theory-policy coordination degree of some influencing factors is relatively low.At the end of the paper,some corresponding policy optimization paths are proposed.

［Purpose/significance］ Starting from the scientific response to major emergencies,gather intelligence wisdom,explore the theory and method of risk perception and prediction of major emergencies,comprehensively improve the ability to perceive the evolution of major emergencies and predict derivative risks,and promote the whole process of major emergencies emergency management with intelligence decisionmaking［Method/process］ Based on the research concept of dual data and knowledge driving,and on the basis of revealing the evolution mechanism of major emergencies by using the theory graph,this paper defines the risk of major emergencies and the risk factors of major emergencies in combination with relevant researches at home and abroad,and constructs the risk transmission link model of major emergenciesThis paper puts forward the specific method and implementation process of sensing and forecasting the risk of major emergencies by using the risk transmission link,and carries out an empirical study based on the “7·4 rainstorm” event in Wanzhou,Chongqing［Result/conclusion］ The empirical study shows that the theory,method and implementation process of risk perception and prediction of major emergencies based on the event evolutionary graph proposed in this study are highly scientific and operable,and can provide intelligence support for relevant emergency management when similar major emergencies occur

［Purpose/significance］ The renaming of the first-level discipline has brought brand new opportunities and challenges,and analyzing the current situation and feasible development approaches of information science is of great practical significance to the future construction and development of the discipline of information science.［Method/process］ This paper reviews the development and transcendence of the information resource management school of Chinese information science,analyzes the internal and external development dilemmas of Chinese information science in the context of the renaming of the first-level discipline based on the analysis of changes in the disciplinary affiliation,the competition between the related disciplines and the expansion of the discipline,and the differences in the paradigm of the different schools of information science,and combined with the current development of the discipline to explore the future development path of Chinese information science in the framework of the first-level discipline of information resource management.［Result/conclusion］ The research results indicate that the development of Chinese information science under the framework of the first-level discipline of information resource management needs to focus on the intrinsic logical connection between the second-level disciplines,i.e.,DIKW resource management,to expand the different basic theory system of information resource management,and around the logical chain of expanding the new,guarding the correctness,and integrating the common advancement,to promote the information science as a kind of management discipline based on information resources,to carry out the education of weakly sensitive intelligence literacy integrated with the training of intelligence thinking,and to speed up the construction of a comprehensive knowledge system and methodology system of information science.

［Purpose/significance］ The study of humanAI interaction with embodied intelligence extends the traditional humancomputer interaction,emphasizing the understanding and adaptation of embodied artificial intelligence to human needs and behaviors,covering technology optimization,user experience,privacy security and ethical issuesThe article discusses the theoretical basis,application practice and future development of embodied intelligence in humanAI interaction experience,which provides an important reference for understanding its complexity,promoting technological progress and application innovation［Method/process］ Through systematic review,the article analyzed 561 related literatures from 2015 to 2024,constructed an analysis framework of “theoretical development technical application future prospect”,deeply analyzed the multidimensional characteristics and application of the related research on the interactive experience of embodied intelligence［Result/conclusion］ The research of embodied intelligence in the interactive experience of humanAI shows the characteristics of interdisciplinary integration,technical diversity and wide application,and it shows great application potential in many fields,such as smart medical care,smart manufacturing,autonomous driving and smart pensionThe article puts forward a framework of humanAI interaction experience based on embodied intelligence,and looks forward to the future research direction,including the theoretical development of digital drive,the method innovation of multidisciplinary integration,the scene expansion of technology application and the establishment of social ethics norms under human factors engineering,which provides practical enlightenment for the healthy development of humanintelligence interaction with embodied intelligence

［Purpose/significance］ In complex environment,open source defense data has different structures and complex semantics,so it is urgent to integrate multimodal semantic information timely and effectively to assist intelligence decisionmakingThis paper proposes a multimodal national defense data fusion model to enhance the capability of national defense intelligence analysis［Method/process］ Firstly,the development of open source intelligence is sorted outSecondly,the complexity of defense data environment is analyzedThirdly,the key technologies of multimodal data fusion are summarized,and the fusion model is constructedFinally,combined with the multimodal defense data fusion case,the corresponding fusion enlightenment is proposed［Result/conclusion］ In complex environment,multimodal defense data fusion should not only accurately grasp the granularity of semantic fusion,but also take into account the needs of intelligence tasks,and combine deep learning to achieve fast and accurate fusion of open source data

［Purpose/significance］ The present study aims to construct a health information recognition model based on large language models and knowledge graphs,with the intention of enhancing the accuracy and reliability of health information identification［Method/process］ Initially,a knowledge graph was constructed utilizing public health information datasets published on authoritative platforms,serving as domainspecific knowledgeSubsequently,five experimental groups were designed,including Decision Tree,Support Vector Machine,Logistic Regression,GPT,and KGLLMFinally,a verification sample consisting of 552 annotated misinformation items from an authoritative rumorrefutation platform was employed for experimentation,and a comparative analysis of the results from the five groups was conducted［Result/conclusion］ The KGLLM model for identifying false health information demonstrated exceptional performance in terms of accuracy,achieving a rate of 9835%This result represents an improvement of 1478%,324%,and 1233% over the Decision Tree,Support Vector Machine,and Logistic Regression models,respectivelyCompared to the GPT model,the KGLLM model also exhibited an accuracy increase of 480%Moreover,the KGLLM model outperformed the GPT model on other evaluation metricsThese findings conclusively substantiate the role of knowledge graphs as domain knowledge in mitigating the illusions present in LLMsThe integration of large language models with knowledge graphs to enhance the accuracy of health information recognition

［Purpose/significance］ Food security is the foundation and important content of national security.The emergency intelligence system is an important support for emergency management.The construction of food security emergency intelligence system can provide scientific solutions and efficient operation guarantee for dealing with food security emergencies.［Method/process］ Firstly,the normative research method is used to explain the relevant concepts and summarize the existing research.Secondly,based on the analysis of food security emergency intelligence needs,the key elements of the system are refined,and the intelligence service,large model agent platform architecture and organizational structure are discussed in detail in combination with the cloud edge architecture.Finally,the mode operation process of food security emergency intelligence system based on large model agent is expounded.［Result/conclusion］ The food security emergency intelligence system based on large model agent intelligently aggregates intelligence services,intelligently adapts to multi-agent needs,and intelligently assists emergency decision-making.It not only provides full-life cycle intelligence support for food security emergency management,but also lays the research foundation of large model agent in the field of emergency intelligence,thus contributing to the modernization of emergency management and the maintenance of national food security.

［Purpose/significance］ Driven by modern science and technology,interdisciplinary research has become an important way to solve complex problems and create knowledge in the scientific field［Method/process］ Overview of relevant core concepts,definition of interdisciplinary knowledge diffusion,and comprehensive review from three dimensions:measurement,process characteristics,and influencing factors of interdisciplinary knowledge diffusion［Result/conclusion］ Most existing studies use academic literature as the main data source,and use citation relationship chains to design singledimensional and multidimensional indicators to measure interdisciplinary knowledge diffusion;citation content analysis is currently the main direction for analyzing the diffusion process and characteristicsIn addition,knowledge,subjectivity and environmental factors often have synergistic and variable mechanisms of action on the diffusion process and resultsOn this basis,a conceptual model of influencing factors of interdisciplinary knowledge diffusion is constructed to improve the efficiency and effect of interdisciplinary knowledge diffusionEmpirical research provides new theoretical referencesAlthough the development level of each research direction is basically the same,relevant research methods and data still need to be further enriched and optimizedFuture research should deepen the understanding of the relationship between interdisciplinary and knowledge diffusion to promote the organic combination of interdisciplinary research management and scientific innovation work and keep pace with the development of the big science era

《情报学进展》第15卷经过两年的酝酿终于面世了，由中国国防科学技术信息学会主持出版，《情报理论与实践》编辑部承担选题策划与组织工作。该书是一本反映情报学和信息技术应用领域研究进展的年度评论，涉及一段时期情报学重点领域及前沿热点问题，总结所取得的成果及未来发展趋势。内容上选取在国内外有一定研究成果，或有一定应用的选题，在一定程度上揭示了近年来情报学的研究现状、热点与趋势，利于回顾并引导相关研究。主要内容有：数据计量学的学科构建及其发展趋势、面向国家战略的情报学教育体系建设、公共危机信息管理研究进展与趋势、数智赋能背景下情报学研究进展、国内外算法风险研究进展、数据隐私风险的识别与消减——以医疗数据为例、开放科学时代学术评价研究的新机遇与新挑战——从系列开放获取宣言/倡议或行动计划谈起、人工智能赋能情报研究的变革与发展、数智时代的知识组织研究进展、企业家发现的情报学探索：基于情报学视角的“企业家发现”模型、学科主题探测与演化分析研究述评、2022—2023年情报学前沿进展综述以及2022—2023年度情报学专业动态等。

［Purpose/significance］ ROK is the first country to promote the MyData system into applicationROK’s practice and exploration in the field of personal data management,especially in the model of promotion in MyData,can provide useful reference for the improvement of our personal data management and application system［Method/process］ In combination with the development of digital government in ROK,this paper uses literature research and comparative politics research methods to discuss the concept and connotation the system of MyData,and examines the application and effect of MyData in the public and financial fields from the perspective of national strategic measures implemented by the digital platform government［Result/conclusion］ As a new personal data management model,MyData plays a positive role and influence on the protection of personal data rights and interests,the innovation of government public services,and the circulation and utilization of data assetsIn terms of balancing the relationship between the full use of personal data and the maintenance of data security,MyData system has an important theoretical and practical significance with great institutional,technical and market value

［Purpose/significance］ This study aims to ensure national food security using information science methods,enhance the professionalism of think tank services,and promote service innovation and upgrading in information and library institutions.［Method/process］ By conducting online surveys and interviews,the study summarizes the shortcomings of existing think tanks in supporting food security policy consultations and analyzes service tasks.Proposing an think tank service model and implementation path for food security policy consultation based on multiple streams theory.［Result/conclusion］ The think tank service model constructed in this study can accommodate the complex logical relationships of food security issues.It responds to policy consultation needs through content Q&A,briefing services,and solution services,thereby promoting the realization of scientific and high-quality think tank services.

［Purpose/significance］ The aim is to explore the functional implementation of a think tank for food security policy consultation.By analyzing and mining policy texts,it seeks to provide scientific advice to policymakers,enrich the theoretical framework of policy informatics,and offer a reference for intelligence to play a think tank role in the field of food security policy consultation.［Method/process］ By integrating text semantic analysis techniques such as the BERTopic model and knowledge association computation,a text analysis scheme is proposed based on enacted policies,agenda policies,and proposed policies.This approach aims to uncover policy themes and evolution trends,and match reasonable recommendations to agenda policies based on text similarity.［Result/conclusion］ This study analyzes the tasks,methods,and processes of applying policy text analysis to the services of think tanks for food security policy consultation.Through data collection and empirical analysis,it successfully uncovers key themes in Chinese food security policies,evaluates trends,and supports think tank recommendations,providing new perspectives for think tank policy research.

［Purpose/significance］ This study explores the influencing factors and formation process of privacy paradox in the quantified-self scenario,in order to help solve the dilemma of personal information protection,promote the digital ecological governance of health management platform,and also provide a new perspective for the theory and practice of the interaction between user and platform.［Method/process］ This study used mobile experience sampling method to collect data,and the target subjects were selected for semi-structured interviews through rank sum test.After that,the interview data was analyzed by three-level coding to extract the influencing factors of the privacy paradox in the quantified-self scenario.［Result/conclusion］ There are four dimensions to quantify the influencing factors of privacy paradox in quantified-self scenario:context,task,conflict and coordination.Privacy paradox arises from the evolution process of “privacy boundary change-privacy disclosure behavior-privacy paradox”,and privacy boundary change plays an important role in the formation of privacy paradoxes.

［Purpose/significance］ Identifying key core technologies is a challenge that must be faced in the process of technology breakthrough.Explore the key core technologies of each application in the industry from the perspective of patent application,which is of theoretical and practical significance for enterprises to seek technology breakthrough.［Method/process］ Take the patent as a bridge to construct the “technology-application” co-occurrence relationship;adopt the Leiden cluster discovery algorithm to categorize the technologies according to the application similarity of technologies,which in turn clarifies the characteristic technology classes of each application;adopt the comprehensive index evaluation method to evaluate the key core degree of the application technologies,and take the technologies with the TOP 15 key core degree of each application as the alternative set of the key core technologies;recognize the technologies in the alternative set of key core technologies that belong to the characteristic technology classes of each application as key core technologies for each application.［Result/conclusion］ Identify the key core technologies of each application in the industry by combining the technical differences among applications,and provide useful references for enterprises to identify the key core technologies from the overall level.

［Purpose/significance］ This paper examines the causal factors and action routes of information cocoon in the application of generative artificial intelligence for researchers,discusses the formation mechanism of information cocoon for researchers,and guides researchers in using generative artificial intelligence to assist scientific research［Method/process］ Firstly,the factors contributing to the information cocoon in the application of generative artificial intelligence by researchers were identified from relevant literature and expert interviewsThen,using the ISM model method to classify the factors into hierarchical levels,proposing hypotheses and constructing an information cocoon causal factor model based on relevant research,and finally,based on the structural equation model method,the constructed model and the proposed hypothesis are verified［Result/conclusion］ The research results show that information literacy,information filtering technology,and information recommendation technology all have a significant positive impact on information selection preferences.Information literacy has a significant positive impact on information homogenization,while information filtering technology and information recommendation technology have no significant impact on information homogenizationInformation selection preference,information homogenization,and information overload have a significant positive impact on the formation of information cocoons,and information overload plays a mediating role in the formation of information cocoons between information selection preference and information homogenization

［Purpose/significance］ The purpose of this paper is to clarify the differences in the understanding of the concept of intelligence failure and accurately understand and define the connotation and extension of the concept of intelligence failure,promotes the academic community to reach a consensus on the definition of intelligence failure and provide support for further deepening the research on intelligence failure.［Method/process］ Through combing the mainstream literature in Chinese and English,the author compares and analyzes the basic understanding of the concept of intelligence failure at home and abroad,and explores the relevant controversial issues to give a targeted response.［Result/conclusion］ Defining intelligence failures as errors made by intelligence agencies in the course of intelligence production and distribution,counterintelligence,and other intelligence activity operations is more consistent with its essential nature.The inappropriate use of intelligence by decision-makers is more a matter of decision-making than intelligence,and thus should not be categorized as an intelligence failure.The term intelligence failure should not be translated as intelligence oversight,but rather as failure of intelligence,which is more appropriate.In the case of accurately caring for the subtle difference between intelligence failure and intelligence error,the translation intelligence failure may also be used selectively to a certain extent.

［Purpose/significance］ Explore effective methods to improve the performance of automatic hierarchical classification and crosslanguage classification of literature resources［Method/process］ Treat literature resource classification as a classification code generation task,use the library’s cataloging data to construct training datasets and test datasets,conduct parameterefficient finetuning of the large language models,such as ChatGLM 3 and Llama 2,on the training dataset,and analyze the classification performance of the model on the Chinese and English test datasets［Result/conclusion］ In different output formats,finetuning the large language model to directly output the classification code can obtain the optimal classification performance;as the number of training samples increases,the classification performance of the finetuned large language model continues to improve;the accuracy of the finetuned large language model based on 22000 samples can reach 08848 and 05076 respectively for the firstlevel category and complete classification code of Chinese Library Classification,which is better than the general large language model;the large language models trained on Chinese literature resources can effectively classify English literature resources,and the classification performance is only slightly lower than that of Chinese literature resourcesA small number of the classification codes generated by the large language model are not valid Chinese Library Classification Codes

［Purpose/significance］ Study on EU data policy system aims to identify key directions,points and strategies for construction of data policy system,and promote the development of data-related theories and methods.［Method/process］ By combing and summarizing policy texts,main components of the policy system were described and analyzed from aspects of the overall guidance of digital transformation,the panoramic setting of data strategy,the construction of data rules,the guidance of multiple data scenarios,and the guidance of data practice optimization.［Result/conclusion］ Thus,the characteristics and limitations of the EU data policy system are analyzed from the main body,policy form,construction orientation and content points,and some revelatory strategies are put forward based on reality of our country:deepen the collaborative leadership mechanism of data institutions,strengthen the construction of multiple rules guided by data laws and regulations,fully integrate the overall requirements of national development,and integrate the layout based on data elements and data governance frontiers.

［Purpose/significance］ Against the backdrop of increasingly intense global technological competition,open source intelligence has become a crucial tool for researching and predicting global trends in science and technology,highlighting its growing importance in scientific and technological intelligence workAs a significant data source and analytical target for scientific and technological intelligence,science and technology project data exhibit multisource and multimodal characteristicsConducting indepth analysis and mining of such data to support management and decisionmaking activities represents an essential approach to the efficient utilization of scientific and technological resources in the new era［Method/process］ This paper integrates the intelligence workflow with the multimodal knowledge graph construction process,proposing a framework for constructing multimodal knowledge graphs based on open source science and technology project dataThe framework comprises four key components:demand analysis,open source intelligence collection,multimodal science and technology project knowledge graph construction,and knowledge graph servicesEach component’s core elements are discussed in detail［Result/conclusion］ Using the multimodal data from publicly available projects of the Intelligence Advanced Research Projects Activity (IARPA) as a case study,a multimodal knowledge graph was constructed following the proposed frameworkThe graph includes seven types of entities—projects,institutions,personnel,technologies,documents,images,and videos—along with various relationshipsIn the future,multimodal knowledge graphs can be integrated with questionanswering systems and recommendation systems to provide more intelligent intelligence services for science and technology management and decisionmaking

［Purpose/significance］ In the context of global aging,elderly care institutions have emerged as pivotal settings for smart eldercare.These institutions generate vast amounts of data through their service provision,yet much of this data remains underutilized and unexplored.To address this gap,it is essential to develop and refine mechanisms that facilitate effective data sharing among multiple stakeholders.［Method/process］ This study developed a datasharing model for smart elderly care institutions by analyzing four key components:participating stakeholders,the content of shared data,the levels of the sharing environment,and the methods of sharing.Furthermore,the study proposed a collaborative pathway for data sharing within the information ecosystem of smart elderly care institutions.This pathway was analyzed through the lenses of both the stakeholder chain and the activity chain to identify effective strategies for implementing data sharing.［Result/conclusion］ The findings highlight that for the datasharing xmodel in smart elderly care institutions to function effectively,it is crucial to first enhance the data mining and analytical capabilities of the supporting big data platforms,thereby increasing both the efficiency and quality of data processing.Additionally,establishing and improving data security mechanisms is vital.Clear definitions of data privacy boundaries are necessary to ensure that the personal privacy and data security of the elderly are rigorously protected throughout the datasharing process

［Purpose/significance］ The rapid development of generative artificial intelligence represented by ChatGPT brings great opportunities for the intelligent transformation of information retrieval.［Method/process］ Explore the function principle of enabling information retrieval by ChatGPT,analyze the compatibility between ChatGPT supporting technology and information retrieval,evaluate ChatGPT by using the expert scoring method,analyze and evaluate ChatGPT’s ability level in the field of information retrieval,and take four scenarios of government affairs,academic,teaching and business as examples.The application of ChatGPT empowering information retrieval is further revealed.［Result/conclusion］ Starting from the four levels of the resource layer,processing layer,application layer,and optimization layer,it is proposed to promote the development process of information retrieval by customizing the information set of professional fields,focusing on the ability of information extraction,building the dual-engine structure of “search superimposed ChatGPT” and strengthening user interaction.

［Purpose/significance］ As a new type of production factor,fully developing and utilizing data resources and expanding the application scenarios of standardized data are the necessary means to release the value and activate the potential of data elements.［Method/process］ According to the idea of “scene identification-model design-model interpretation”,and the qualitative analysis method is used to identify the coding scenes of textual data,to form the classification system of data application scenes.The data application scenario model is constructed by combining innovative application cases,data life cycle theory,CRISP-DM model and data value chain,and the data application scenario model is explained from top to bottom in the three dimensions of demand-oriented,data-supporting and technology-driven.［Result/conclusion］ We form a classification system covering 4 first-level scenarios,14 second-level scenarios and 41 third-level scenarios,construct a scenario model framework that is demand-oriented,data-supported and technology-driven,and analyze and explain the logic and connotation of the model in depth to provide reference and guidance for broadening the application scenarios of normalized data.

［Purpose/significance］ The digital society has put forward new requirements for the development of core literacy of college students.It is necessary to further clarify the connotation of AI literacy and construct an AI literacy evaluation index system for students in colleges and universities,so as to provide reference support for the assessment of students’ AI literacy development status,ability improvement and cultivation.［Method/process］ From the perspective of the literacy continuum,the study systematically reviewed the origin and development of AI literacy,and through the deconstruction and reorganization of the content and elements of the continuum,mapped it to the construction of the index system of AI literacy.Then,we constructed an AI literacy evaluation framework for college students based on the KSAVE model and defined the connotation of elements through literature research.And then,the Delphi method was used to consult on the preliminary construction of the evaluation index system for AI literacy,and the analytic hierarchy process was used to determine the weight of evaluation indicators.［Result/conclusion］ An evaluation system for college students’ AI literacy consisting of 5 first-level indicators and 19 second-level indicators is constructed.The cultivation strategy of AI literacy is proposed from the three aspects of cognitive position,internal driving path and diversified scenario creation.

［Purpose/significance］ Identifying and analyzing the key influencing factors of social media users’ false information verification behavior (FIVB) is of great significance for motivating users’ FIVB,improving the false information governance system,and promoting the healthy and sustainable development of the Internet information ecology［Method/process］ The article constructed a model of factors influencing social media users’ FIVB by applying qualitative metasynthesis,risk information seeking and processing model,and media context theory,followed by identifying and analyzing the key influencing factors in it by using the DEMATEL method［Result/conclusion］ The study shows that:① The model of influencing factors of social media users’ FIVB is mainly composed of 4 dimensions and 20 influencing factors,such as user factors,media factors,information factors,and contextual factors② The influencing factors interact with each other to form a complex network system③ The 11 influencing factors,such as user information literacy,media authority,and media popularity,are the key influencing factors of social media users’ FIVBBased on this,we propose optimization strategies to motivate users’ FIVB and improve the false information governance system

Purpose/significance The issue，as revealed by the public’s difficulty in locating specific policy content on government portals and traditional policy websites，reflects not only the low perceived accessibility but also the limited social value of disclosed government information. To address this issue，this paper proposes a policy knowledge graph framework based on multi-factor semantic relevance to improve data organization and enhance the social value of government information disclosure. Method/process Utilizing a knowledge graph as the technical framework，this study employs models such as BERTopic，KeyBERT，and BERT-BiLSTM-CRF to refine the granularity of policy text information. Semantic fine-grained information is then used to calculate the similarity and relevance of policy texts to identify related policies. The knowledge graph is constructed and stored using Neo4j. Result/conclusion Visualization and policy relevance tests demonstrate that the proposed semantically relevant knowledge graph provides more relevant and accurate policy information compared to traditional policy databases，meeting users’ needs for high-value information retrieval. Limitations The method is currently limited to policy text data. Future research could focus on improving the processing of multimodal government data，strengthening cross-domain data integration and application capabilities，and enhancing the applicability and generalizability of the constructed knowledge graph.

［Purpose/significance］ In the context of great power games,counter intelligence has become a key component of national security workAnalyzing the US National Counterintelligence Strategy from a national security perspective is of great significance for the theoretical exploration and practical development of China’s national security intelligence［Method/process］ Study the strategic vision and national security motives of the US National Counterintelligence Strategy,analyze its strategic release agency,strategic system background,and intelligence threat landscape;thoroughly analyze the vision,tasks,pillars,and objectives of the National Counterintelligence Strategy;explore its counterintelligence mechanism under national security thinking and gain strategic insights for developing counterintelligence work in the national security system［Result/conclusion］ The US National Counterintelligence Strategy takes counterintelligence as the cornerstone of national security strategy,emphasizes the offensive and defensive nature of counterintelligence work,coordinates the art and technology of integrating intelligence,and provides useful inspiration for China in integrating counterintelligence into the national security system,formulating strategic guidance and toplevel design,and building counterintelligence work mechanisms

Purpose/significance Exploring research topics in the field of Information Science and Library Science （ISLS） and analyzing their evolution paths in detail is of significant theoretical and practical value for understanding the discipline’s development，revealing the progression of its knowledge system，and guiding innovative advancements in the field. Method/process This paper uses data from CSSCI-indexed journals in the ISLS field published between 2019 and 2024. Based on initial literature grouping and direction extraction using hypergraph spectral clustering and TF-IDF，we apply a dynamic topic model to analyze research topics and their evolutionary paths in different groups，further uncovering the development trends and characteristics of each research topic. Result/conclusion The research directions in the ISLS field exhibit broad and diverse characteristics，which can be classified into nine categories，including online social and health information behavior，national intelligence and strategic competition，and open science and data policy governance. Through dynamic topic modeling，40 research topics were identified，with significant attention given to topics such as the evolution of public opinion dissemination，national emergency intelligence and strategic decision-making，academic influence evaluation，social media and privacy perception，and technology identification analysis. Moreover，there are intrinsic connections and intersections among topics across different research directions. From the perspective of topic evolution，the hot topics are closely related to social development，technological advancement，and policy guidance，exhibiting strong temporal characteristics. The integrated framework combining hypergraph clustering and dynamic topic modeling not only effectively captures the complex higher-order semantic structures within knowledge networks but also enables a fine-grained dissection of each research topic. Limitation This paper only employs hypergraph spectral clustering to differentiate literature groups，and dynamic topic modeling has limitations in capturing both long-term and short-term evolutionary characteristics of topics. Further research is needed to explore these aspects.

Purpose/significance This study aims to explore effective multi-actor collaboration mechanisms to promote the efficient construction and value realization of smart senior care data resources，thereby enhancing the quality and efficiency of smart senior care services. Method/process An exploratory single-case study method was employed，focusing on the practical work of FiberHome HsiangYun Company. To achieve data triangulation，multi-source data were collected through field investigations，semi-structured interviews，and online surveys. A theoretical analytical framework was constructed based on Collaborative Innovation Theory and the “Three Bodies and Two Directions”model. Under this framework，content analysis was used to conduct an in-depth analysis of the data. Result/conclusion The research reveals the subjects，objects，and carriers in the construction of smart senior care data resources. It extracts a multi-actor collaboration framework and a three-dimensional operation model for the construction of smart senior care data resources. From the perspective of multi-actor involvement，this study provides both practical experience and theoretical insights for the construction of China’s smart senior care data resource system.

［Purpose/significance］ Public data constitutes a vital component of data elements.Investigating the efficiency of the multiplier effect of public data is instrumental in examining the performance of China’s data element multiplier effect,analyzing the reasons affecting its effectiveness,and providing guidance for the practice of open utilization of public data.［Method/process］ This study defines the conceptual connotation of the efficiency of the multiplier effect of public data and constructs a multidimensional inputoutput indicator system.Adapting the DEA model,an empirical analysis is conducted on elderly care theme data of sample platforms to examine the technical efficiency,scale efficiency/effect,and redundancyinsufficiency rate of the multiplier effect of public data.［Result/conclusion］ The efficiency of the multiplier effect of public data in China exhibits three issues:low resource utilization due to lagging management and technological levels,low output returns due to insufficient resource scale,and redundancy and insufficiency due to unreasonable allocation structures.Based on these findings,suggestions are made to enhance management efficiency,coordinate open operations,strengthen policy and institutional guarantees,expand the scale of resource investment,optimize resource allocation,and foster an ecosystem for the open utilization of public data,thereby comprehensively enhancing the efficiency of the multiplier effect of public data

［Purpose/significance］ This paper proposes a technology topic identification method that combines BERTopic model finetuned with scientific literature domainspecific Pretrained Language Model and Large Language ModelThe proposed method dives into learning the semantic features contained in the content of scientific literature,identifies technology topics from unstructured scientific texts,evaluates and interprets the content of identified technology topics to generate topic labels automaticallyBy reducing manual intervention and further improving the accuracy and validity of technology topic identification,the proposed method can provide theoretical and tool support for expanding and enriching the research method system of technology topic identification［Method/process］ The paper proposed a novel method framework for generating technology topic representations which consists of three core stepsFirst,the FinetunedBERTopic model was built to identify the technology topics hidden in the scientific literatureIn the FinetunedBERTopic,the scientific literature document was converted to its embedding representation using a scientific domainspecific pretrained language model named PAT SPECTER and the semantic relationship between technology tokens were modeled using KeyBERT to generate the complete technical phrases in topic representationsThen,the identified technology topic contents were evaluated and interpreted to generate topic labels automatically using a Large Language Model named GPT4o and prompt engineeringLastly,based on this,take the domain of generative artificial intelligence as an example to verify the effectiveness of the method in this paper［Result/conclusion］ Experimental results show that the method proposed in this paper effectively improves the accuracy of technology topic identification and significantly reduces manual intervention,achieving more efficient technology topic extraction across a variety of benchmarks involving LDA,Top2Vec,BERTopic and other models

［Purpose/significance］ Data security has become a major issue concerning national security,economic development,and social governanceEstablishing a data security risk early warning intelligence system at the national level is of critical significance in preventing major data security incidents［Method/processe］ First,based on existing research and regulatory practices,the concept of national data security is defined,its risk characteristics are explored,to form a basic understanding of the early warning intelligence systemSecond,a theoretical framework for the national data security risk early warning intelligence system is designed,including four main functional modules:knowledge base and risk reasoning identification,comprehensive risk assessment,risk prediction and early warning,and intelligence service platformFinally,from the methodological perspective of “WuliShiliRenli” Approach,taking the data security of generative artificial intelligence as an example,the implementation path of the risk early warning intelligence system is planned［Result/conclusion］ The national data security risk early warning intelligence system is essentially an organic integration formed by the deep collaboration of human expert wisdom,data and knowledge systems,and intelligent technological tools in the entire process of intelligence workIt can provide rapid and accurate intelligence services for national data security prevention and governance

［Purpose/significance］ Based on the Cynefin framework,the integration of complexity leadership theory reveals the internal logic of knowledge hoarding formation in community of practice,which has important theoretical value and practical significance for understanding the knowledge-leading system and the enabling holistic function of complexity leadership in community,so as to build the knowledge hoarding formation process model and governance mechanism.［Method/process］ According to the characteristics of knowledge and the complexity of environment,the community of practice is divided into different knowledge Spaces.In the knowledge space,the paper discusses the process of knowledge hoarding at the individual and environment levels in the community under the effect of complexity leadership,so as to build a knowledge hoarding formation process model,and proposed a specific knowledge hoarding governance mechanism.［Result/conclusion］ There are four types of knowledge hoarding formation processes in community of practice:compulsive hoarding,restrictive hoarding,adaptive hoarding and perceptual hoarding.It proposes governance mechanisms such as decentralization,diversification,collaboration and intervention governance to adjust knowledge hoarding and enhance knowledge interaction function to adapt to the dynamic changes of the environment.Knowledge subject,object and environment shape the knowledge ecology of the community of practice,and make full use of the interaction of various elements to avoid and regulate knowledge hoarding,which is conducive to forming the advantage of multi-source knowledge resources and providing resource guarantee for the good operation of the community.

From a historicism perspective and based on literature review,this paper analyzes the origin,boundaries,key research issues and core components of information scienceIt defines information science as “a discipline that studies the management,analysis,processing,growth,correlation,and dissemination of information in a developing technological environment,as well as the acquisition,sharing,development and utilization of information by individuals and organizations to meet their personalized needs” It proposes that the core components of information science include LIS,informetrics,informatics and social informatics,and intelligence study and engineeringIt analyzes three origins of information science:the European documentation information school,the Soviet Union’s scientific communication school,and the American information science schoolIt proposes that information science is a fundamental as well as an applied interdiscipline driven by information technology and widely serving economic and social developmentIts core goal is to “study how to solve the contradiction between the limitations of human information processing capabilities and the infinite growth of information”,and suggests that compared to “information resource management”,“information science” is a more appropriate name for the first level discipline

［Purpose/significance］ In the context of accelerating the transformation of knowledge organization and service,the humanAI (artificial intelligence) collaborative knowledge innovation model has become increasingly prominent,and has become a key engine to promote the “emergence” of knowledge generationIt is essential to identify the core elements of humanAI collaborative knowledge innovation and dig out its influence laws and mechanisms to further improve humanAI collaborative knowledge innovation［Method/process］ Based on the paradigm of “CASA”,this study constructs a research framework of humanAI collaborative knowledge innovation,and attempts to set relevant variable parameters according to the knowledge flow law of the simulation experiment to simulate the humanAI collaborative knowledge innovation mechanism［Result/conclusion］ It is found that the knowledge innovation system of humanAI collaboration includes three subsystems:human,generative artificial intelligence (GAI),task and environmentKnowledge externalization level and knowledge interpretation level are important means to further drive humanAI collaborative knowledge innovation,humanAI trust can improve the amount of knowledge innovation by adjusting the level of humanAI collaborationGAI knowledge innovation threshold also constrains humanAI collaborative knowledge innovation