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

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

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

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

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

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

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

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

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

[Purpose/Significance] Peer review serves as a pivotal quality assurance mechanism in academic knowledge production, encompassing implicit semantic insights within reviewers’ comments. Using text classification models to identify and analyze the semantic features in comment texts can deepen our understanding of the peer review process, illuminate the opaque processes of peer review, and ultimately enhance this crucial system. [Method/Process] This paper introduced an “aspect-intention” semantic mining framework to delineate the specific aspects of papers that reviewers scrutinize and the intentions underpinning their comments. Leveraging data from the open peer review journal eLife, it constructed an annotated dataset DAIPR_V1. It then trained and tested text multi-classification models based on SciBERT to identify the aspects and intentions of reviewers’ comments. Finally, it analyzed the semantic features based on the classification results. [Result/Conclusion] The analysis reveals that reviewers predominantly focus on the empirical aspects of papers, followed by presentational and theoretical elements. In terms of intention, reviewers commonly give instructions, urging authors to clarify their work, provide additional experiments or evidence, and make editing and formatting revisions. This is followed by evaluative and summarizing comments, with multiple instructions integrated within a single comment. This paper also underscores the correspondence relationship between the aspects of reviewers’ comments and their underlying intentions. By exploring the semantic features from the perspective of “aspect-intention” correlation, this paper provides a rich perspective for understanding the peer review process, and deepens the comprehension of peer review as an important form of academic communication.

[Purpose/Significance] Investigating the policy configurations of international preprint stakeholders can aid in understanding the current policy environment in which preprints are developing, thereby providing a reference for the formulation of preprint policies in our country. [Method/Process] By integrating the TOE theoretical framework with the fsQCA method, this study distilled the preprint policy elements from 40 research and educational institutions, academic publishing institutions, and scientific funding institutions, and revealed and analyzed their policy configurations. [Result/Conclusion] The results indicate that research and educational institutions are more inclined towards “organization-environment” configurations, academic publishing institutions are primarily “technology-environment” configurations, and scientific funding institutions tend towards environment-led configurations. Finally, policy recommendations are proposed for stakeholders of preprints in our country from the three dimensions of technology, organization, and environment.

[Purpose/Significance] In the digital era, the importance of public data as a new resource is increasingly prominent, and how to activate the potential of public data and release the value of public data is of great significance to promote the development and application of big data and empower innovation-driven development strategies. [Method/Process] Based on the concept and connotation of public data, and the open data ecosystem theory, this paper constructs an analysis framework for the public data value release from “resource-subject-environment”, and applies the fuzzy set qualitative comparative analysis method to carry out configuration analysis to explore the linkage effect of multiple factors on the release of public data value. [Result/Conclusion] The study concludes three modes of public data value release, including user-oriented, government-led, and full-ecological demand. Based on this, a targeted value release optimization path is proposed to achieve the goal of maximizing the value release of public data.

[Purpose/Significance] Constructing the cultural digitalization innovation evaluation index, assessing and monitoring the innovation level across provinces can provide references for promoting the in-depth development of cultural digitalization in China. [Method/Process] Through expert scoring method and entropy weight method, this article constructed a cultural digitalization innovation index system. Combining patent data and industry data, it made an empirical analysis on the level of cultural digitalization innovation in 31 provinces. [Result/Conclusion] The empirical results indicate that the level of cultural digitalization varies across provinces. Economically developed provinces show higher level of innovation, and some provinces exhibit distinctive innovation characteristics. Cultural digitalization innovation presents regional differentiation and industrial cluster differentiation. The innovation level is highly coordinated with scientific and technological talents, intellectual property layout and other elements. It puts forward the following suggestions: focus on the core of national cultural digitalization construction, effectively guarantee the openness and sharing of data and cultural resources; strengthen the dynamic monitoring in provinces and regions, and encourage the full excavation of cultural resources; accelerate and deepen the innovation activities, and pay attention to the absorption of talents in related industries.

[Purpose/Significance] This study investigates documentation requirements in cultural heritage policies to understand their overall status, main content, and future development trends. [Method/Process] The study adopted network literature survey and policy content analysis to code and analyze 148 policy documentation requirements related to cultural heritage documentation in China. [Result/Conclusion] It finds that, with the development of these policies in China, the framework of policies has been formed, including the strong demand of documentation, the synergistic participation of multiple stakeholders, expanding and detailed documentation objects, access-oriented cultural heritage archiving activities, and sustained and complete safeguard measures. Overall, documentation is becoming an indispensable and fundamental part of cultural heritage protection. In the future, it is necessary to further strengthen the systematization and relevance, the professionalism and digital transformation-oriented design of policies.

[Purpose/Significance] With the rapid development of artificial intelligence generated content (AIGC), it is necessary to recognize the misconduct behaviors that exist in the process of AI-generated content. This paper aims to provide a theoretical reference for effective AIGC governance and create a healthy and safe development environment. [Method/Process] By establishing AIGC quality standards, this study analyzed specific misconduct behaviors in AI-generated content and constructed a governance mechanism for AIGC misconduct based on the WSR system methodology. [Result/Conclusion] This paper describes AIGC misconduct behaviors from four dimensions: data, expression, ethics, and law. Then it proposes a governance path for AIGC misconduct based on the WSR system methodology from the perspective of Wuli, Shili and Renli. It constructs a multi-agent synergistic governance mechanism integrating data, algorithms, technology, auditing, supervision, laws, and regulations, providing a reference for relevant departments to develop AI governance measures.

[Purpose/Significance] Against the backdrop of the intensifying U.S. semiconductor technology restrictions on China, it is strategically imperative to delve deeper into the intricate operational chains and dynamic evolutionary patterns embedded in the impact of U.S. technology export controls, assisting decision-makers to gain insight to the evolution paths of policy impacts, gauge the effectiveness of the countermeasures, and update their policy planning. [Method/Process] This study proposed a method for identifying the evolution paths of policy impact based on event evolutionary graph. From the perspective of the dynamically evolving nature of the events, it introduced the Markov chain model to identify critical evolution paths of events in the graph. It analyzed the impact of U.S. technology restrictions on major associated entities across the upstream, midstream, and downstream segments of China’s semiconductor industry and their evolution trends, thereby assessed the complex mechanisms influencing various stakeholders. [Result/Conclusion] The findings reveal that there are significant differences in the evolution characteristics of events among entities at different sectors of the industry chain. Government-led pre-interventions pose a crucial impact on the positive orientation of event evolution, while market-responsive events have an important feedback role in the paths. Consequently, it is imperative to prioritize policy implementation to develop a multi-level, full-chain policy system encompassing the entire industry, foster the collaborative efforts of government, industry, academia, and research to advance breakthroughs in key core technologies within the semiconductor field, and promote cooperative synergy among enterprises across the upstream, midstream, and downstream sectors to establish a secure, autonomous, and collaboratively innovative semiconductor industry ecosystem.

[Purpose/Significance] With the rapid growth of data volumes and technological advancements, leveraging intelligent technologies for earlier and more precise identification of emerging research topics is of great importance. This paper reviews relevant literature to provide a more precise and multi-perspectival methodological reference for future research on the emerging research topics identification. [Method/Process] Using the Web of Science Core Collection and CNKI as data sources, this study first clarified emerging research topics and related concepts, summarized the multi-source data used in the research. It then focused on reviewing the identification methods, emphasizing those with currently low application but high potential in science and technology intelligence analysis, and provided a comprehensive overview. Finally, the paper proposed feasible directions for the emerging research topic identification. [Result/Conclusion] Emerging research topics have always been a frontier hotspot in scientific intelligence, with increasingly clear characterizations and rapidly iterating identification methods. However, current research faces challenges such as single data types and a lack of advanced identification methods and tools. Future research needs to expand theoretical perspectives, enhance the use of intelligent technologies, cover more dimensions of emerging research topics, and integrate expert knowledge to improve the accuracy and recall rate of emerging research topic identification.

[Purpose/Significance] This paper summarizes the main contents of the U.S. OSTP national OA policy, analyzes the implementation mechanism of the new version of the national OA policy in the United States, judges the strategy understanding and policy propositions of the United States regarding OA, and proposes enlightenment and suggestions for China. [Method/Process] Utilizing the National Open Access Policy documents issued by the U.S. OSTP, this study conducted a comprehensive examination and systematic analysis of the U.S. National Open Access Policy, focusing on its policy content and implementation mechanisms. Additionally, it incorporated the research reports submitted to Congress by the OSTP and recent practical developments to evaluate the U.S. government’s strategy understanding and policy propositions regarding open access. [Result/Conclusion] The United States has elevated open access to the level of national strategy and comprehensively promoted the implementation of the new version of the national open access policy. China should also re-examine the significance of formulating its national open access strategy, clarify its policy proposals on open access, design scientific reasonable policy content, accelerate the introduction of open access policies, and establish relevant supporting measures to promote policy implementation.

[Purpose/Significance] This study aims to construct an evaluation index system for the sense of personal information security, providing a reference for scientifically assessing the public’s sense of personal information security. [Method/Process] Based on social cognitive theory, this study clarified the conceptual connotation and dimensions of the personal information security sense. Then, the evaluation index system was constructed using a combination of literature review, grounded theory, Delphi method, and analytic hierarchy process (AHP). An empirical analysis was taken to assess the public’s sense of personal information security. [Result/Conclusion] The evaluation index system for the sense of personal information security comprises five primary indicators: self-stability in personal information security assessment, self-efficacy in personal information risk response, satisfaction of personal information security needs in interpersonal communication, perceived control over personal information processing activities, and behavioral tendency towards personal information security. Additionally, it includes 11 secondary indicators and 42 tertiary indicators. The study finds that the public’s sense of personal information security exhibits distinct distribution characteristics in terms of index scores and demographic differences.

[Purpose/Significance] In the context of digital intelligence transformation, this paper analyzes the trend and challenges of intelligence work, proposes a logical framework for empowering intelligence work with trustworthiness to provide a reference for the development of information science. [Method/Process] The paper analyzed the development of intelligence work under digital transformation from the perspective of the “information turn”. On this basis, it summarized the challenges encountered during intelligence collection, analysis, and service. It then clarified the trustworthiness standards for intelligence work and constructed an empowerment logic framework from three dimensions: thinking domain, management domain, and process domain. This framework was to enhance the trustworthiness of empowerment while ensuring its efficiency. [Result/Conclusion] By leveraging the combined efforts across various dimensions, including trustworthy thinking, trustworthy assessment, trustworthy disclosure, discrimination mechanisms, interpretative mechanisms, and adaptive mechanisms, it is helpful to effectively address the challenges of trustworthiness in intelligence work, such as the discernibility of intelligence collection, the explainability of intelligence analysis, and the self-adaptability of intelligence services, thereby aligning with the development of the “information credibility shift” “ information computation shift” and “information integration shift”. Moreover, future research should further address key issues in the construction of the trustworthiness empowerment logic framework, including the development of intelligence trust theory, the identification of trustworthy methods in intelligence, and the refinement of intelligence support mechanisms.

[Purpose/Significance] This paper attempts to put forward the concept of intelligent data to provide ideas and path references for data intensive and data-driven S&T intelligence work under the new paradigm. [Method/Process] This paper comprehensively summarized relevant intelligence work practices, analyzed and defined the concept and characteristics of intelligent data, clarified its generation and circulation mode, and put forward its construction principles, construction and service mode. And then, it explored the construction and service of intelligent data facing S&T strategic decision-making scenarios in the form of typical cases. [Result/Conclusion] Intelligent data is the “scientific research data” in the process of intelligence research and service, and is the core production element of data-driven intelligence research and services, which mainly includes three types, namely, intelligence raw data, intelligence core data, and intelligence derived data. It condenses the precise understanding and insights of intelligence personnel on strategic needs, contains longterm accumulation and precipitation of intelligence service. Intelligent data is characterized by decision scenario orientation, embedded expert wisdom, rich data types, high intelligence value density and strong extensibility (SERVE). Its construction should be guided by decision-making scenarios and deeply coupled with decision-making problems. The construction process should follow the principle of experience to intelligence, explicit to implicit, and result-oriented to process-oriented, and the aim of data storage, methods reuse, evidence-based conclusion and knowledge transfer. It is carried out from four aspects: decision-making scenario preset and analysis, decision-making problem combination and solution formulation, intelligent data construction, intelligence service effectiveness feedback and data upgrading. Taking the construction of intelligent data in the context of S&T strategic decision-making such as export control and major S&T issues as examples, this paper expounds the idea of intelligent data construction and the service effect of strategic intelligence work driven by it.

[Purpose/Significance] This paper analyzes the current situation of smart reading services on academic platforms, and explores how AIGC technology can empower libraries with smart reading services. It aims to provide a reference for upgrading smart academic reading services in libraries. [Method/Process] This paper adopted content analysis to conduct two rounds of coding analysis on smart reading services provided by nine typical academic platforms. The analysis focused on five indicators: reading material supply, auxiliary reading, reading applications, reading communication, and behavior management. In response to the existing problems and considering the entire reading process for academic user, this paper proposed a path for AIGC technology to empower smart academic reading services in libraries. [Result/Conclusion] Big data and artificial intelligence technology are promoting the smart services of academic platform in the reading materials supply, auxiliary reading, and reading applications. However, the application of these technologies in reading communication and behavior management remains limited. In the “five situations” of reading: seeking, reading comprehension, reading application, reading communication, and reading behavior management, AIGC technology can empower smart academic reading services in libraries in five aspects: high-quality academic resource, reading cognitive strategies, writing assistance, reading communication, and reading behavior management.

[Purpose/Significance] With the growth of intelligent decision-making application scenarios, explainability research has gradually become a hot topic. In order to clarify the current research status of explainability in intelligent decision-making and propose feasible paths, reviews the relevant literature on explainability of intelligent decision-making from the perspective of human-computer interaction. [Method/Process] This article used content analysis method for literature coding, and summarized the three main types of literature in this field, four types of explainable information output, and evaluation indicators from both system and user aspects. [Result/Conclusion] Through literature review, a hierarchical framework for explainability of intelligent decision-making is proposed, which divides explanation into three levels: reactive explanation, interactive explanation, and meta explanation. The level of explainability can be improved through explanation evaluation, interaction design, effect testing, and heuristic intervention.

[Purpose/Significance] In the face of the transformative wave of science agents reshaping research productivity, S&T documentation and information service (DIS) institutes urgently need to explore how to deeply integrate science agent technology with DIS works to accelerate the enhancement of the capabilities and upgrading the service quality of DIS works. [Method/Process] Based on 518 papers related to scientific intelligence agents from arXiv, this study revealed the current development and characteristics of science agents from two dimensions: domain distribution and research themes. The findings suggested that the development of specialized agents based on multi-agent collaboration is an inevitable choice for various disciplines to embrace science agent technologies. In response to this insight, and by integrating the evolving needs of DIS work in the digital and AI era with a universal agent framework, this paper designed a general framework for DIS agent. It further deconstructed the key tasks in building DIS agent, considering both the technological adaptability required during the development phase and the system security challenges in the application phase. Additionally, the study examined the profound impact of DIS agent on the transformation of DIS work paradigms. [Result/Conclusion] The multi-agent collaborative DIS agent consists of six core components: DIS cognition models, general foundational resources, planning and reasoning, configuration files, large models, and memory. When constructing DIS agent, attention should be focused on six key areas: construction of reliable knowledge bases with multimodal standard alignment, research and development of tool technologies corresponding to information method models, development of modular agents for information contexts, risk testing of action plans for DIS agent, comprehensive evaluation of system performance of DIS agent, and supervision, regulation, and security governance of DIS agent. In the future, driven by DIS agent, the paradigm of DIS work will shift from a human-centric model to one of human-multi-agent collaboration, enhancing the efficiency and intelligence level of intelligence work.

[Purpose/Significance] Although personal traffic data is classified into three levels based on the degree to which data leakage or illegal use may harm individual rights and interests, there is currently a lack of specific quantitative basis and grading results. This study identifies personal traffic data items and measures the privacy value of personal traffic data, providing a theoretical basis for data grading. [Method/Process] Firstly, this paper classified traffic privacy text types and built a privacy text library as a source of identification. Secondly, it mined privacy text library, analyzed syntactic structure and language components, and established a traffic sensitive word list as a recognition model. Finally, it analyzed the factors affecting the privacy of traffic data, established a privacy measurement model, and measured the privacy value of traffic sensitive data. [Result/Conclusion] Research shows the ranking of personal traffic data privacy values from high to low is as follows. Personal track data and personal traffic violation data (traffic violation records, traffic integrity records) have the highest privacy value. Personal transportation payment data (transportation service purchase and fine payment, transportation insurance payment) and personal basic data (identification data, semi-identification data, biometric data, network identification data, property data, health data) have a secondary privacy value. Personal transportation operation data (passenger ticket, transportation card) have the lowest privacy value.

[Purpose/Significance] Reviewing the typical regulatory models for the open utilization of healthcare data both domestically and internationally and dissecting the advanced practices in the supervision of foreign healthcare data open platforms can provide references for improving the regulatory level of healthcare data in our country. [Method/Process] Employing the methods of online surveys and case analysis, this study dissected the current status of healthcare data supervision both domestically and internationally. The study selected the representative American platform OpenNeuro to analyze its regulatory strategies during the stages of data collection, storage, and utilization, summarized successful experiences based on the four dimensions of subject specification, data security, data quality and data openness. [Result/Conclusion] Suggestions are put forward for promoting the regulatory practice of healthcare data open utilization in China from four aspects: establishing an inclusive and prudent multi-level regulatory model, promoting the collaborative participation of multiple subjects in data regulatory, improving platform regulatory of the entire data lifecycle, and focusing on the balance between data utilization and security protection.

[Purpose/Significance] As pre-trained models continue to demonstrate astonishing capabilities, more and more researchers are introducing BERT into the field of intelligence analysis, leading to a trend of evolution from a single BERT model to a fused BERT model. However, the problem of inexplicable prediction results of pre-trained language models poses some risks to the algorithms generalization in the field of intelligence analysis. [Method/Process] This article took the BERT algorithm, which was widely used in intelligence analysis, as an example. Using significance theory, it calculated the Token Embedding significance of the hidden layer state values inside BERT and explored the key factors that affected the final classification results. Finally, taking the team data security policy classification intelligence analysis project as an example, it visualized and deeply analyzed the BERT’s interpretability in it. [Result/Conclusion] The visualized interpretation model, based on gradient saliency, provides clear insights into the running status of each BERT layer. By re-labeling misclassified samples, the accuracy of the validation set is improved from 96.74% to 97.78%. It also indicates that this method can effectively guide the dataset annotation in policy text classification tasks and provide reference for the wider application of this model in the field of intelligence analysis.

[Purpose/Significance] Digital feedback is a teaching and supporting behavior of the younger generation to the older generation in digital access, use and literacy. It has become an important path to bridge the intergenerational digital divide and promote digital inclusion in the context of social digitalization and aging population. Systematically revealing the research progress of digital feedback at home and abroad can provide useful reference for further promoting the research and practice of digital feedback. [Method/Process] Systematic review and content analysis methods were used to sort out and review literature related to digital feedback. [Result/Conclusion] The main content of digital feedback research involves seven aspects: concerned groups, dimensions and contents, occurrence fields, formation process, influencing factors, value utility and promotion strategies. Based on the logical integration of research contents, the “5W1E1H” framework of current digital feedback research is formed, and relevant topics should be continuously promoted from theoretical research and practical action in the future.

[Purpose/Significance] To explore the mechanisms of value co-creation in library knowledge services involving multiple stakeholders can promote the innovation and enhance the effectiveness of library knowledge services. [Method/Process] This study analyzed and organized the stakeholders, processes, and influencing factors of value co-creation in library knowledge services. It constructed a theoretical model of value co-creation in library knowledge services and employed the system dynamics method to investigate the mechanisms of the value co-creation stakeholders and their influencing factors. [Result/Conclusion] Simulation results indicate that during the process of value co-creation in library knowledge services, the completeness of the institutional framework has a decisive impact. The greater the number of stakeholders participating in value co-creation, the higher the efficiency of knowledge services and the more significant the improvement in user capabilities. The benefits of value co-creation in library knowledge services become significantly apparent only after a prolonged period of coordination, accumulation, and interaction among multiple stakeholders.

[Purpose/Significance] The term “Tu Shu Guan” in Chinese is the most fundamental and pivotal term in library science in China. Its etymological attributes represent one of the significant issues that cannot be ignored in the study of Chinese library history. The objective of this paper is to elucidate the etymology of the term “Tu Shu Guan” to delineate its dissemination in China and Japan, and to ascertain its linguistic attributes, which will facilitate a more profound understanding of Chinese library history. [Method/Process] This paper used methods of textology, bibliography, and etymology to review the academic history and examine its initial documentary evidence for the term, and examples of its use during the Ming and Qing dynasties. As books were the most important carrier for the dissemination of the term, a systematic analysis of Huang Tingjian’s poems in Japan was conducted to investigate the annotation and publication activities of the poems and to analyze the stereotypes and popularity of the term “Tu Shu Guan” in China and Japan in the modern era. The etymological attributes of the term were then argued from an etymological point of view using the etymological research method. [Result/Conclusion] From an etymological perspective, it can be argued that a term is a “returned word” (Sino-Japanese interactive word), as long as a term originally appeared in Chinese literature, was later introduced to Japan, and was adopted by the Japanese during the Meiji period as a translation of a Western term. Thus, the term “Tu Shu Guan” is not a “Japanese word” but a “returned word,” or “Sino-Japanese interactive word”.