[Purpose/Significance] In the context of deep integration of technology and culture, this study explores the cultural content production empowered by AIGC. It aims to fully understand the transformation of content production mode and the improvement in service innovation capabilities brought by AIGC to GLAM, and provide a reference for the application of AIGC in GLAM. [Method/Process] Building upon a review of previous research, this paper proposed a GLAM content production mechanism empowered by AIGC, covering technical support, resource construction, content generation, and service innovation. By analyzing current practical cases, it analyzed the intrinsic mechanisms and characteristics of three content generation modes: auxiliary, applied and creative type. Additionally, this paper summarized the AIGC practical applications in digital collections, digital human, and digital scenarios in GLAM institutions. [Result/Conclusion] AIGC empowerment has positively impacted the business efficiency, scale of production, personalized experiences, and innovation capabilities of content generation in GLAM. GLAM should actively embrace the trend of AIGC to improve management and service efficiency, provide users with efficient and accurate Q&A and recommendations, as well as emotional interaction and display. Overall, it will accelerate the digital transformation and upgrading of GLAM.

[Purpose/Significance] In the context of the inevitable trend of digital intelligence transformation of public cultural services, it is essential to analyze the existing issues and challenges faced by public cultural institutions in China to offer effective recommendations for their future development. [Method/Process] By mining digital intelligence-related content and user behavior information published by public cultural institutions on social media platforms, this study explored the attention and implementation levels of digital intelligence in their services. It further examined the audience’s focus and sentiment tendencies towards the digital intelligence of public cultural institution services in application scenarios, especially in AIGC (Artificial Intelligence Generated Content). [Result/Conclusion] Currently, the overall attention and implementation of digital intelligence by public cultural institutions still require enhancement. Public museums exhibit relatively higher levels of attention and implementation towards digital intelligence. Users’ attention to the digital intelligence of public cultural institution services is mainly reflected in intelligent robots, virtual digital humans, three-dimensional cultural relics, exhibition viewing, and AI modeling of cultural relics, and their overall sentiment tendency is slightly negative. Public cultural institutions should adapt to user demands, actively improve their digital intelligence services, and enhance the development of their digital intelligence services.

[Purpose/Significance] Exploring content production models and key experiences based on GLAM digital integration services helps drive high-quality digital cultural content production under the trend of GLAM integration, as well as promoting service innovation. [Method/Process] This paper employed online surveys and literature research methods, using Europeana, DPLA, DigitalNZ, and the National Public Cultural Cloud as case studies, to comprehensively analyze the underlying content production models and experiential characteristics of the GLAM digital integration services. [Result/Conclusion] GLAM digital integration service platforms primarily encompass four types of content production models: AI-empowered content production, data aggregation-based content production, crowdsourcing-based content production, and online-offline interactive content production. Based on these models, a comprehensive content production model for GLAM integrated platforms has been constructed. Furthermore, considering the current content production practices of GLAM institutions in China, four suggestions are proposed: strengthening technical infrastructure, establishing unified data standards, expanding diversified funding channels, and enhancing user engagement.

[Purpose/Significance] Data-enabled intelligent transformation and knowledge discovery have become new growth points for libraries to maintain development vitality and innovate service concepts. The efficient aggregation, orderly organization, integrated utilization and open sharing of massive multi-modal and heterogeneous data in libraries through data governance have become an important driving force for the intelligent transformation of libraries. [Method/Process] Based on the needs of smart libraries in regard to data management, services, and analysis and mining, this article analyzed the connotation, problems and challenges of library data governance under the background of intelligence transformation. [Result/Conclusion] It proposes a project-driven and application-driven implementation of a library data governance system. Based on the smart library management system, the data-enabled library smart transformation goal, and the principles of “data standardization, assetization, knowledge, and intelligence”, it suggests optimizing and controlling data platform architecture, data governance organizational mechanism, data standard specification system, asset management and operation mode, full-process data security and compliance governance, and data integration application. It aims to ensure data governance can better support the development of smart libraries and facilitate the intelligence transformation of library undertakings.

[Purpose/Significance] The fourth-generation evaluation theory, with its core concept of collaborative construction, has driven the change of scientific research evaluation thinking. Under the background of this theory, the evaluation of the research impact also pays more attention to the process of impact generation and dissemination, and emphasizes the interactions of different stakeholders in the process. [Methodology/Process] Driven by both the categorized evaluation system at the policy level and the change of evaluation theory at the theoretical level, this study proposed the categorized evaluation idea of selecting evaluation subjects based on the content attributes of scientific knowledge. It further verified the rationality of this idea through real case data. This study took REF2021 case data as the main source of analysis, and employed prompt learning to assist manual identification of government, enterprise, university and public stakeholders. Based on it, it explored the differences in the participation of different stakeholder types in the research impact generation process in terms of the distribution of participation and cognitive themes. [Result/Conclusion] The results demonstrate differences in the subjective cognition and realistic participation levels of the four stakeholder types in the research impact generation process. On the basis of the confirmed rationality of evaluation ideas, this study proposes suggestions for the selection of evaluation subjects based on disciplinary category from the specific case data, and provides new practical ideas for academic evaluation practices in China.

[Purpose/Significance] In the context of national cultural digitization strategy and digital China construction, digital memory projects have become a new research and practical hotspot. Exploring the construction path of digital memory in universities will provide new ideas for academic inheritance and civilizational development in the digital age, and offer valuable reference for governments, enterprises and other institutions, undertaking digital memory projects. It has important theoretical and practical significance. [Method/Process] This article extensively reviews and draws on the construction experience of global cultural memory projects and relevant theories in the field of digital humanities. Based on the theoretical-level strategy formulation and macro-analysis of digital memory projects in universities, this study investigated the practical aspects of resource development, project operation, organizational structure, and working mechanisms based on first-hand experience with the operation and management of Chongqing University’s digital memory project. It explored and discussed the suitable project operation mechanisms, organizational structure, and working mechanisms for university digital memory projects. It demonstrated the construction achievements under this operation mechanism, and looked forward to the future service models for digital memory in universities. [Result/Conclusion] A good operating mechanism is the key to the success of digital memory in universities. However, further consideration should be given to aspects such as technological innovation and training, academic cooperation and exchange, marketing and fund-raising, as well as refinement of content and display. At the same time, different universities should consider their unique cultural backgrounds, disciplinary strengths, resource availability, and target users, and conduct comprehensive design in terms of target positioning, implementation plans, team organization, and service models. Digital memory is of great significance to universities and should be continuously promoted as a long-term basic function of universities to achieve its far-reaching impact and lasting results.

[Purpose/Significance] Taking the course of “Practical Skills of Scientific and Technological Information Retrieval and Utilization” as an example, the research carries out empirical research on teaching practice of integrating the ideological-political elements into the course, to provide reference for the same type of information literacy education. [Method/Process] According to the teaching characteristics in professionalism, practicability and general education, the research designed the path of integrating the ideological-political elements into the course from four aspects, including teaching objectives, teaching contents, teaching methods and teaching techniques. And it introduced effective methods to put the concept into the teaching practice and to realize the organic combination of professional courses and ideological-political education. [Result/Conclusion] The questionnaire survey shows that integrating the ideological-political elements into this course has achieved certain educational effectiveness, and it will continue to be explored and optimized in the future.

[Purpose/Significance] Adolescents are the main force in maintaining cybersecurity and the force of future digital citizens. Their digital communication literacy has become an important factor influencing the information security in cyberspace. This article constructs a scientific and reasonable framework and implementation path for the adolescent digital communication literacy to improve the level of cybersecurity governance in the digital age. [Method/Process] From the perspective of competency theory, combined with domestic and foreign governance practices, this paper constructs a “ Four Forces” model, which includes perceived identity, skill operation, creative participation and collaborative development, as the core. This model serves as an analytical framework to cultivate the adolescent digital communication literacy and maintain their cybersecurity improve the network information security ability. [Result/Conclusion] It is necessary to build an inner, supportive, and environmental barrier for cultivating the adolescent digital communication literacy by strengthening their digital communication governance skills, improving the digital communication system, and creating a safe and healthy digital ecosystem. Effectively enhancing the adolescent digital communication literacy and security governance will help build a digitally strong China.

[Purpose/Significance] The construction of quality evaluation index system of AIGC is helpful for users to identify high-quality AIGC and AIGC service providers to improve content quality. [Method/Process] The original data were obtained through literature retrieval and user interviews, and were encoded at three levels based on grounded theory to extract the quality evaluation indexes of AIGC. On this basis, a questionnaire survey and analytic hierarchy process were used to determine the weight of each index, and the quality evaluation index system of AIGC was constructed. [Result/Conclusion] The quality evaluation index system of AIGC includes 4 first-level indexes such as content characteristics, expression characteristics, utility characteristics and technology characteristics, along with 21 second-level indexes such as personalization, efficiency, intelligibility and interpretability. Among these, content characteristics have the highest weight and the greatest impact on AIGC quality. In addition, the study finds that AIGC, PGC and UGC have some similarities and differences in the evaluation of information quality. Traceability, humanism, plasticity and interpretability are unique indexes of AIGC quality evaluation.

[Purpose/Significance] This study explores the cognitive transition characteristics of users in the exploratory search process and analyzes the users’ cognitive changes under different task types and search intentions. It contributes to a further understanding of the learning mechanism in the exploratory search process. [Method/Process] An experiment was used to record the participants’ search process on the video screen. The think-aloud method was used to collect the participants’ descriptions of the search process. The questionnaire gathered data on the participants’ personal information, task perception, and task answers before and after the search. Through coding of the video and textual data, the article analyzed the length and probability of users’ cognitive transiting paths across different task types, and the characteristics of these paths with different search intents. [Result/Conclusion] This study finds that the cognitive transition path is the shortest when searchers take procedural tasks. Searchers mostly initiate their cognitive transitions from a state of “understanding”, and application is the demarcation point between ascending and descending cognitive states. Analysis of user cognitive transition paths reveals significant variations across different search intents. Paths associated with information collection and information assessment exhibits the highest degree of complexity.

[Purpose/Significance] Exploring the influencing factors and mechanisms of users’ continuous usage behavior on audiobook platforms can enrich the theoretical system of user behavior research, and provide theoretical reference for the improvement of audiobook platforms. [Method/Process] This paper adopted a procedural grounded theory to conduct coding analysis on interview data, systematically refining the three-level factors influencing user behavior on audiobook platforms. It clarified the “storyline” of the relationship among various categories and constructed a model of factors influencing users’ continuous usage behavior on audiobook platforms, specifically encompassing 7 main categories, 24 basic categories, and 103 initial concepts. [Result/Conclusion] The results indicate that physical and mental disabilities, audiobook platform design, reading experience, usage and switching costs, as well as multi-dimensional information content presentation have direct impacts on users’ continuous usage behavior on audiobook platforms. Additionally, they exert indirect effects through satisfaction. Furthermore, physical and mental disabilities, audiobook platform design, and multi-dimensional information content presentation influence the reading experience. Based on these findings, strategic recommendations for optimizing ecosystem and e services of audiobook platforms are proposed from a supply-side perspective.

[Purpose/Significance] Identifying emerging topics in disciplinary fields can not only guide researchers in selecting scientific topics, but also provide the technical support for the precise formulation of strategic emerging industry development plans. [Method/Process] Due to the lack of a unified definition for “emerging topics” and the challenges associated with processing complex, high-dimensional data in topic identification, this study proposed an emerging topic detecting method based on topic popularity evolution. It combined the keyword importance, average similarity coefficient and affinity propagation clustering algorithm to adaptively identify research topics in a field. The topic popularity was characterized by the novelty, influence and potentiality of topics. Time series of the topic popularity were obtained by skyline algorithm and principal component analysis method, and the emerging topics were accurately identified by the time evolution of the initial topic popularity. [Result/Conclusion] By data processing and mining journal papers in supply chain from 2012 to 2021 in the China National Knowledge Infrastructure (CNKI) database, this study demonstrates that the proposed method can effectively identify emerging topics in the field. It provides decision-making support for relevant researchers and government departments in selecting topics and planning.

[Purpose/Significance] This study aims to extract structured item information from free-text clinical scales using ChatGPT without annotations, which efficiently advances the structuring and intellectualization of medical scale resources. [Method/Process] A framework for item information extraction was defined, including eight attribute types and considering the structural differences in clinical scale measurement concepts. A dataset was constructed by collecting 59 commonly used clinical psychometric assessment scale documents. Zero-shot prompt templates were designed based on measurement concept levels, and experiments were conducted using the official ChatGPT-3.5 and ChatGPT-4 interfaces. The extraction performance and possible influencing factors of different ChatGPT versions in processing different clinical scale texts were analyzed from multiple perspectives. [Result/Conclusion] The extraction performance for scale item sources is the best, with Micro-F₁ and Macro-F₁ scores of at least 98.90% and 97.83%, respectively. This is followed by response options, instructional guidance, and scoring rules, with item numbers and instructions showing moderate performance. Clinical explanations have the lowest performance, with Micro-F₁ and Macro-F₁ scores of 47.73% and 45.51%, respectively. ChatGPT-4 performs better overall, but the recall rate of some attributes is weaker than that of ChatGPT-3.5. The increase in measurement concept levels, dimensionality, number of items, and text length are found to reduce model performance. In summary, ChatGPT can efficiently assist in the structuring of medical scale resources, especially when dealing with simple scales.