[Purpose/Significance] The advent of the Internet and the subsequent evolution of new technologies and applications, such as big data and artificial intelligence, have spurred the exponential growth of a new generation of technologies. China has entered the era of data-driven digital intelligence, with social network data privacy protection playing a crucial role in the country's comprehensive security strategy. By studying the evolution of this field, we gain insights into how to protect personal information, foster the healthy development of social platforms, and facilitate the responsible circulation of data elements. Compared to previous studies, this paper offers a broader range of perspectives, exploring the main directions and roles of each element of privacy protection with the information ecology theory, and more comprehensive research content, and combining causes, technologies, management and metrics.We propose an ecological framework for social network data privacy protection, based on a thorough overview of the subject matter. This framework serves as a reference point for the evolving landscape of privacy protection practices. [Method/Process] This study uses two different approaches: literature review and content analysis. The former is utilized to identify and categorize literature related to CNKI and WOS, while the latter is employed to visually analyze and interpret this corpus using Citespace. This study provides a systematic review of data privacy protection in social networks in four dimensions: privacy protection triggers, privacy leakage, privacy protection technology, and privacy protection management. The review is based on the visualization and analysis of both Chinese and international literature. Furthermore, we present our perspective on information ecology, integrating analyses of research themes and limitations for each information topic. We also explore strategies to promote the sustainable and healthy development of behaviors related to data privacy protection in social networks. [Results/Conclusions] Interdisciplinary exchange on data privacy protection in social networks is essential to advance the digital intelligence era. Relying solely on isolated methods of privacy protection is insufficient in the face of an increasingly complex application environment and the trends towards digitalization and intelligence. It is therefore necessary to establish a comprehensive privacy protection system that integrates technical optimization, legal improvements, platform regulations, and user engagement. Specifically, from a technical perspective, it is essential to leverage a variety of technologies to develop solutions for privacy protection. From a legal perspective, there is a need to refine the content, standardize the adjudication process, and strengthen supervision and sanctions. At the platform level, optimizing the content of privacy policies and ensuring their effectiveness are crucial. Finally, at the user level, it is essential to raise awareness of privacy protection and to enhance privacy protection capabilities. Moreover, it is crutial to examine the inherent relationship between each entity and the methods of protection. A key limitation of this paper is the lack of an in-depth analysis of the interaction mechanisms between stakeholders within the ecological framework of social network data privacy protection. Future iterations will address this by incorporating a background on the complex information environment and conducting a more in-depth analysis of the interaction mechanisms.

[Purpose/Significance] Interdisciplinary research has emerged as a key driver of knowledge innovation, its essence being integration of knowledge from different disciplines. A deep and nuanced understanding of the research content of interdisciplinary knowledge integration is essential to foster innovation beyond traditional academic boundaries. Most of the research reviews on interdisciplinary research summarize theories, concepts and indicators from the macro level, while the content of interdisciplinary knowledge integration at the micro level is scattered, and lacks systematicity and logic. Therefore, this study attempts to classify and summarize the research methods, research content and research ideas involved in order to provide reference for scholars and researchers engaged in interdisciplinary knowledge integration. [Method/Process] Based on Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) database as the primary data sources, we reviewed the relevant literature on interdisciplinary knowledge integration. By clarifying the intrinsic meaning of interdisciplinary knowledge integration, we have systematically reviewed and summarized the existing research findings from three aspects. First, research on the degree of knowledge integration mainly involves measurement methods. Second, research on the content of knowledge integration is based on citations and keywords. Third, research on the process of knowledge integration involves its integration path and process, and the characteristics of the integration stage. On this basis, this paper also summarizes the limitations and challenges of existing research, and provides research perspectives for subsequent research on interdisciplinary knowledge integration. [Results/Conclusions] The existing results have extensively explored the definition, measurement method, content, and process of interdisciplinary knowledge integration, but there are problems such as limited applicability of knowledge integration measurement methods, insufficient semantic disclosure, and the lack of systematic research on the degree of knowledge integration. Future research in this area should pay attention to the following three aspects. First, the applicability of methods for measuring interdisciplinary knowledge integration should be improved in order to better adapt to the development of interdisciplinary knowledge integration. Second, there is also a need to strengthen the study of knowledge integration from the perspective of knowledge increment, examining how new knowledge is created and how it contributes to the advancement of the area. In addition, efforts should be made to explore new theories and methods, grasp the development law of interdisciplinary knowledge integration, and expand the application scope and application value of interdisciplinary knowledge integration.

[Purpose/Significance] In the context of the rapid development of artificial intelligence and content generation (AIGC) technology, it is particularly urgent and important to explore in depth its impact and evolutionary path on the information culture of university libraries. As a central platform for knowledge dissemination and information exchange, university libraries not only hold a wealth of literature resources, but also serve as important places for teachers and students to obtain information and improve their information literacy (IL). Therefore, the study of the internal logic and development ideas of information culture in university libraries under the influence of the AIGC aims to reveal how new technologies can reshape the information service model of libraries, and how to promote the deep integration of knowledge innovation and educational informatization by optimizing organizational structure and improving service efficiency. This study will provide scientific basis for university libraries to formulate strategic plans that adapt to future development trends, help them to better serve teaching and research in the context of the new era, and cultivate high-quality talented people with high IL skills. [Method/Process] This study focused on both theory and practice of library information culture construction. First, the theoretical foundations of library information culture are considered, and the concept, characteristics, and manifestations in university libraries are systematically reviewed. Second, an in-depth analysis of the impact mechanism of the AIGC technology on information culture was conducted, including changes in information acquisition methods, improvements in information processing capabilities, and innovations in information exchange models. Finally, the integration path of information culture and the AIGC technology was explored, and a framework for cultivating information culture in libraries and at the university level was proposed. [Results/Conclusions] Under the promotion of the AIGC technology, the cultivation of information culture in university libraries has a new trend and characteristics. In order to better achieve the goal of educational informatization, university libraries should actively embrace and respond to change by building information system standards, improving information management systems, enriching information resources, and enhancing information service capabilities. At the same time, they should also promote the cultivation of information culture by integrating information resources for university education, enriching IL systems, cooperating in the development of the information technology, and participating in the construction of information governance systems. By integrating educational resources, cooperating in information technology research and development, and jointly building an open, shared, and mutually beneficial information ecosystem, we can effectively promote the prosperity and development of information culture in university libraries.

[Purpose/Significance] Accurately measuring the influence of technical topics is crucial for decision-makers to understand the developmental trends in the technology sector. It is also an important link in identifying emerging, cutting-edge, and disruptive technical topics. Traditional methods of measuring technical topic influence are significantly affected by the latency of patent data approval and citations, lack a forward-looking perspective on the potential influence of technical topics, and suffer from insufficient semantic richness in the extraction of technical topics. This paper presents a method for measuring technical topic influence based on PhraseLDA-SNA and machine learning. It aims to mitigate the impact of delays in patent data approval and citation, while improving the interpretability and accuracy of the results in assessing technical topic influence. [Method/Process] In this study the explicit and implicit determinants of technical topic influence were first analyzed, based on which an index system for measuring technical topic influence was constructed. Then, the PhraseLDA model was used to extract semantically rich technical topics from a large corpus of pre-processed patent texts and to compute the topic-patent association probabilities. PhraseLDA-SNA enhances the semantic richness of technical topic extraction and deepens the analysis of topic content. Machine learning methods leverage their robust data processing and analysis capabilities to predict the high citation potential of patents related to the topics. This research integrates PhraseLDA-SNA and machine learning methods to accurately measure the significance and advanced nature of technical topics in promoting field development, thereby achieving an accurate measurement of the influence of technical topics. Finally, an empirical study was conducted in the field of cellulose biodegradation to compare the high-impact technical topics identified by the proposed method with those identified by the traditional method. Several experts with high academic influence and extensive experience in cellulose biodegradation research were invited to evaluate the high-impact technical topics identified in this study, thus validating the effectiveness of the proposed method. [Results/Conclusions] Compared with the traditional method, the technical topic influence measurement approach based on PhraseLDA-SNA and machine learning reveals more in-depth content. Moreover, this method also analyzes the importance and leading nature of technical topics, which shows superiority in quantitative analysis. Comparing the distribution of high-impact technical topic-related patents identified by the two methods across different years, the topics identified by the proposed method had a higher association ratio in the most recent data, indicating a significant reduction in the impact of patent data approval and citation delays.

[Purpose/Significance] This study aims to reveal the current state of the electroencephalography (EEG) technology application in the field of library and information science (LIS). By expanding the boundaries of the discipline, it provides insights into the future application of the EEG technology in the LIS field, highlighting its potential to enhance library services and user experience. [Method/Process] The research systematically reviews 65 empirical studies on the application of the EEG technology in the LIS field since the inception of the discipline. These studies were analyzed and organized to reveal the current state of the EEG technology applications in the field. The research examines the methodologies used, the specific applications of EEG in different library environments, and the results of these applications. In doing so, it highlights the role of the EEG technology in the development of intelligent library systems. [Results/Conclusions] This study finds from the 65 literature coding results that the literature on the application of the EEG technology in the LIS field has grown significantly in recent years, with three research foci: first, to study the impact of interface information layout on users' cognitive load and search efficiency; second, to study cognitive behavior in the field of information security; and third, to study the mechanism of followership in human decision making. Future directions and challenges for the application of cognitive neuroscience tools in this area are discussed in order to provide a reference for further applications of the EEG technology in the LIS field. This paper reveals the current research status and characteristics of the EEG technology in the LIS field, fills the gap in the research framework of the EEG technology application, and provides a reference for the further application of the EEG technology. However, the research also acknowledges certain limitations, such as the ambiguity of interpreting EEG research findings in fields such as LIS, and issues related to data privacy and security. These limitations suggest that there are still challenges to be addressed. Therefore, the effective integration of cognitive neuroscience with LIS requires further research and exploration. By providing a comprehensive review and analysis, this study sets the stage for future research that could address current limitations and advance the use of EEG in LIS. The findings underscore the need for interdisciplinary approaches to fully realize the benefits of the EEG technology in understanding and improving user interactions with library systems, ensuring information security, and enhancing decision-making processes in the library context.

[Purpose/Significance] This study aims to unravel the complex relationship between new quality productivity (NQP) and rural revitalization, and to deepen understanding of the role of media in rural development. NQP, characterized by advanced technologies, innovative practice, and enhanced efficiency, has the potential to transform rural economies and communities. This research provides a multi-dimensional theoretical perspective and scientific foundation to advance comprehensive rural revitalization in China. By offering novel insights compared to the existing literature, this study establishes its significance in the field of scientific knowledge and demonstrates its potential to address significant real-world challenges. Understanding the synergies between NQP and rural revitalization can help policy makers, researchers, and practitioners to develop effective strategies to promote sustainable rural development and address socio-economic disparities. [Method/Process] The study employed a rigorous methodological approach that involved the training of a naive Bayes classifier to categorize the texts of government work reports. This machine learning technique enabled the extraction and analysis of relevant information from a large corpus of textual data, providing a robust basis for further empirical investigation. The study utilized provincial-level data from 2012 to 2022 to construct comprehensive evaluation frameworks for the NQP and rural revitalization. These frameworks included a wide range of indicators reflecting economic, social, and technological dimensions.Statistical analyses included bi-directional fixed effect models and spatial Durbin models, which allowed for a comprehensive exploration of the impact mechanisms and spatio-temporal dynamics of NQP on rural revitalization. The bi-directional fixed effect model helped to control for unobserved heterogeneity and to capture the dynamic interplay between NQP and rural revitalization over time. The spatial Durbin model was particularly useful in identifying spatial spillovers and understanding regional interdependencies. The theoretical underpinnings of this research were grounded in established frameworks in economic development and media studies. Media practice, including information dissemination, community building, and consumption upgrading, were hypothesized to play a crucial role in facilitating the impact of the NQP on rural revitalization. The empirical foundations were derived from robust provincial-level datasets, ensuring the reliability and validity of the findings. These methodological choices ensured a rigorous examination of the complex dynamics between NQP and rural revitalization in different regions over time. [Results/Conclusions] 1) Media factors demonstrated significant complementary relationships with various drivers of rural revitalization. 2) Media practice, centered on information support, community building, and consumption upgrading, has profoundly altered rural production relations and economic bases. 3) Temporally, both NQP levels and rural revitalization showed rapid growth, with annual growth rates increasing. Spatially, the central and western regions showed a stronger impact of NQP on rural revitalization compared to the eastern regions.4) NQP had significant spatial spillover effects on rural revitalization, not only influencing local revitalization efforts but also fostering stronger indirect effects on surrounding areas, thereby promoting regional interlinked development.

[Purpose/Significance] With the development of artificial intelligence (AI) technology, the teaching innovation in higher education driven by digital intelligence technology has gradually gained attention. ChatGPT has brought new opportunities and challenges to the development of higher education and the reconstruction of educational ecology. The purpose of this study is to apply ChatGPT tools to the process of information literacy (IL) education in colleges, so as to create a human-machine collaborative teaching paradigm of IL education in colleges based on ChatGPT applications, promote the innovative reform and improve the teaching efficiency of IL education in colleges and provide reference for the application research of AI tools in the field of higher education in the era of digital intelligence and the development of high-quality IL ducation in colleges. [Method/Process] By combing the relevant literature, on the basis of summarizing the global educational application situation of ChatGPT and revealing the educational theory of ChatGPT, combined with the current teaching problems of IL education in colleges, this paper comprehensively analyzes the application scenarios of ChatGPT in the process of IL education in colleges from the perspective of teachers' teaching and students' learning. At the same time, the study carries out practical teaching comparison, and examines the satisfaction of teachers and students by means of "interview + questionnaire", so as to test the application effect of ChatGPT, summarize the problems in teaching and put forward improvement strategies for teaching. [Results/Conclusions] ChatGPT can effectively promote the innovation of IL education in colleges and improve the teaching efficiency of courses. Teachers and students also give good feedback on the educational application of ChatGPT. The application of ChatGPT can effectively improve teaching efficiency, innovate teaching content, optimize teaching process, improve teaching management, and provide students with more learning options, enhance learning initiative, promote higher-order thinking and scientific research innovation. At the same time, the educational use of ChatGPT will also lead to many problems, such as tool abuse, knowledge misleading, information security, and intellectual property rights. Therefore, we should look at the teaching use of ChatGPT dialectically. On the one hand, we should actively promote and apply ChatGPT; on the other hand, we should also pay attention to the different risks that ChatGPT may cause, and formulate forward-looking instructional management policies and guidelines to standardize the use of ChatGPT, so as to give full play to the educational function of ChatGPT and further promote the reform of IL education and teaching in colleges.