[Purpose/Significance] Smart libraries have become one of the most popular topics in the field of library science and industry today.The theoretical research and practical work on the construction of smart libraries have achieved initial results, and generative AI is also flourishing, participating in the construction of various industries.Therefore, it is necessary to base on current development, set long-term goals, and determine strategies for generative AI to participate in the construction of smart libraries. [Methods/Process] Based on the above reasons, this article elaborated on the key path of smart library construction in the perspective of generative AI from five aspects: spatial upgrading, service building, business restructuring, talent cultivation, and system construction. [Result/Conclusion] It provides reference and basis for introducing generative AI into the next stage of smart library construction.

[Purpose/Significance] This paper aims to explore the types, process, and characteristics of Proxy Health Information Seeking Behavior(PHISB), establish PHISB model, and provide new ideas and methods for health information seeking and acquisition. [Method] ology/Process]In this paper, 18 young students and 18 middle-aged people with the experience of PHISB were selected as the objects, and interviews were carried out around their experience of proxy seeking.Qualitative research methods were used to analyze the interview text data. [Results/Conclusion] The core research findings are as follows: ①PHISB can be divided into three types.②The process of PHISB can be divided into six stages, including: trigger initiating—seeking execution—processing and integration—communication and exchange—adoption influence—follow-up seeking.The process of PHISB is nonlinear and circuitous.③The connection and interaction between proxy seekers and recipients is a unique activity in the process of PHISB, at the same time, there are obvious intergenerational differences and individual differences in PHISB.④The PHISB model is constructed.

[Purpose/Significance] Supervised learning algorithms based on deep learning are currently the main research methods for text classification.However, the training of supervised deep learning algorithms heavily relies on the accuracy of the sample labels.Due to the annotator's experience and subjectivity, sample labels inevitably contain noise.Label perturbation is an effective way to deal with noisy labels.However, noisy label learning algorithms based on label perturbation lack effective utilization of multiple granularity information at present, which limits the performance of the algorithms. [Method/Process] In order to address the problem, the paper proposed a multi-granularity label perturbation algorithm(MGLP), which combined sample-level granularity and category-level granularity perturbation methods.The MGLP algorithm used the idea of meta-learning to learn the fusion weights of different granularity perturbation methods, which could adaptively adjust the fusion weights according to different data characteristics. [Result/Conclusion] The paper conducts experiment on three text classification datasets, including tweet sentiment classification, movie review sentiment classification, and citation intent classification.The results show that the proposed MGLP algorithm effectively improves the performance of deep learning models in text classification tasks and has broad application prospects in information organization and information analysis.

[Purpose/Significance] Big data have significant impacts on social and economic development.This study compares focus of attention and word embedding general picture of big data between academic platforms and social Q&A platforms in China, with the aim of promoting big data research and practice in China. [Method/Process] Word2vec is an emerging neural network word embedding algorithm with low computational cost and high accuracy, and can effectively measure word similarity at both semantic and syntactic levels.Data were first collected from CNKI(China Knowledge Infrastructure)and Zhihu platforms separately to build corpora of academic and social Q&A platforms.Then, the Word2vec models were trained based on these two corpora respectively.Based on the analysis of the most similar words, comparisons of focus of attention of big data between academic and social Q&A platforms were conducted.Finally, dimension reduction and visualization algorithm were employed to conduct comparison of word embedding general picture between two platforms. [Result/Conclusion] The results illustrate the differences of big data between academic and social Q&A platforms.This study innovatively employs the Word2vec neural network word embedding algorithm to conduct a comparative analysis of big data between academic platforms and social Q&A platforms in China, providing a new perspective for big data research.

[Purpose/Significance] The academic paper submission is faced with the problems of journal selection diversity and re-submission, this paper studies the use of machine learning technology to give multi-label recommendations for periodical submission based on the content of the academic paper. [Method/Process] Papers from 8 CSSCI journals in the field of information science in recent 20 years were selected as samples, TextCNN, TextRNN, and pre-trained language model BERT were used for experiments, and the experimental effects under different feature combinations and multi-label setting strategies were compared. [Result/Conclusion] Multi-label classification can reflect the suitability of articles for different periodical, and the pre-trained language model BERT performs best, with F1 reaching 68.99%.

[Purpose/Significance] Aesthetics play a crucial role in shaping user emotional experience, which in turn drives their human-computer interaction behavior. This study aims to explore the relationship between aesthetics and emotion and examine the mechanism of individual interaction perception from an aesthetic standpoint. [Method/Process] Drawing on the SOR theory, the study developed a research model of"interface aesthetics-human body mechanism-aesthetic perception". An experiment was conducted in which participants with varying levels of aesthetic abilities were asked to browse web pages with different aesthetic qualities. Participants were divided into a high aesthetic group and a low aesthetic group based on the Meier Art Judgment Test. All participants were required to browse web pages with both high and low aesthetics, carefully selected from authoritative websites. Eye tracking devices were used to record participants' eye movement behavior, while subjective perception data was collected through emotional and aesthetic scales as well as semi-structured interviews. [Result/Conclusion] The results demonstrated significant differences between the two groups in terms of total fixation duration, fixation count, and average fixation time. The level of interface aesthetics had a significant impact on visual cognitive processing, emotional valence, and aesthetic perception for the participants. Individuals in the high aesthetic group showed greater sensitivity to aesthetic perception, and the emotional tendencies of both groups were more aligned. Furthermore, the aesthetic ability of participants moderated the aesthetic perception of the interface, while the individual organism partially mediated this perception. This study enhances our understanding of the relationship between aesthetics and emotion in human-computer interaction, offering insights into the design of interaction interfaces from an aesthetic perspective and the improvement of user emotional experiences.

[Purpose/Significance] Real-time interaction is an important advantage of e-commerce live streaming over traditional e-commerce from the perspective of interactive ritual chain verifying the influencing factors of user participation behavior has an important reference for the further development of live e-commerce platform and anchors. [Method/process] In the micro-situation, based on the interactive ritual chain, this paper constructed the interactive ritual chain in the context of e-commerce live streaming, explored the influence of interactive ritual chain effect on user participation behavior, incorporated anchors, platforms, and users into the model, and improved the influence mechanism of interactive rituals. [Result/Conclusion] Through empirical research, it is found that the attractiveness of anchors positively affects group solidarity, and the number of fans negatively affects group solidarity and group symbols; the interactive environment of the platform significantly affects group symbols and emotional energy, and convenience significantly affects the effect of interactive ritual chains; users' interest significantly affects the group symbol and emotional energy, and the user's sense of acquisition significantly affects the emotional energy; the interactive ritual chain generates the group symbol and emotional energy and positively affects the participation behavior, the group solidarity has a negative impact on the participation behavior.

[Purpose/Significance] By exploring the relationship between users' personal traits and their willingness to disclose privacy and its internal mechanism, it is expected to help enterprises understand the risk preferences and psychological needs of different individuals, and provide theoretical guidance and reference for the efficient operation of the platform. [Method/Process] Based on the theory of self-construal, this paper explored the differences in individuals' willingness to disclose privacy. Through two experimental studies, the study explored the influence of self-construal on individuals' willingness to disclose privacy, the regulating effect of permission sensitivity on individuals' willingness to disclose privacy of different types of self-construal and its internal mechanism. The first study explored the influence of self-construal on privacy disclosure intention and the moderating effect of permission sensitivity. Study 2 explored the mediating role of regulatory focus in this process and the mediating effect of moderation. [Result/Conclusion] The results showeds that under high permission sensitivity, interdependent self-construal individuals are more likely to stimulate their prevention focus, independent self-construal individuals are more likely to stimulate their promotion focus, and independent self-construal individuals has higher willingness to disclose privacy than interdependent self-construal individuals. However, under low permission sensitivity, individuals with different self-construal types shows a higher propensity to promotion focus, and there is no significant difference in privacy disclosure intention between individuals with different self-construal types. Regulatory focus plays a mediating effect on the relationship between self-construal and privacy disclosure intention, and permission sensitivity significantly moderates the relationship between self-construal, regulatory focus and privacy disclosure intention.

[Purpose/Significance] Explore the complex motivation of users to participate in the information governance of online healthy communities, aiming to improve the enthusiasm and initiative of users to participate in the information governance of online healthy communities, and propose some measures to improve the information quality of online healthy communities from the perspective of users. [Method/Process] Firstly, the motivational factors affecting users' participation in information governance of online health communities were selected based on self-determination theory. Secondly, a questionnaire was designed to collect data according to the selected variables. Finally, QCA combined with NCA method was used to identify the complex causal relationships between users' motivation and users' governance behaviors, and the paper further how each motivational factor combined to influence the generation of users' participatory governance behaviors. [Result/Conclusion] There are three configurations that trigger the occurrence of user participatory governance behaviors, namely, self participation, external stimulation, and community guidance, in which health information literacy, community identity, reciprocal motivation, and community norms are the core conditions. There is a certain substitution between community identity and reciprocal motivation. The configuration of both with health information literacy and community norms can drive users to participate in information governance; In the combination of community identity and community norms, self-efficacy and perceived motivation have little impact on ordinary users' participation in information governance.

[Purpose/Significance] Research on the influencing factors of the services of China's province level government data open platform, aiming to promote the realization of the value of government open data and improve the construction of government open platform. [Methodology/Process] The paper conducted the assessment framework of the services of China's provincial government open data platform, introduced DEMATEL method to establish a model of influencing factors based on China's provincial government open data platform, explored the current problems of China's provincial government open data platform from the four dimensions of platform functionality, data quality, regulations, standards and user support, and put forward corresponding optimization strategies. [Results/Conclusions] Currently, China's provincial government data open platform suffers from insufficient sharing, imperfect user feedback mechanism, and limited support for promoting data utilization, etc. Therefore, improving the service quality of the government data open platform involves optimizing the online functions, guaranteeing the timeliness and diversity of the data, setting up uniform regulations and standards, and focusing on user participation and feedback, which can provide constructive support for bringing the utility of the government data and the positive creativity of the users into play. This can provide constructive support for maximizing the effectiveness of government data and the active creativity of users.

[Purpose/Significance] With the rapid accumulation of medical and health big data, the quality problem has gradually attracted attention. The enlightenment of quality management and improvement of medical and health big data can be obtained through data quality evaluation. [Method/Process] Firstly, the study constructed the quality life cycle model of medical and health big data based on the data life cycle theory. Then, in combination with literature review and its characteristics, formed the quality evaluation index system, and comprehensively determined the index weights by using fuzzy best-worst method and entropy weight method. Finally, used TOPSIS method to sort the quality evaluation results of medical and health big data, which constituted the comprehensive evaluation model. [Result/Conclusion] The index system and comprehensive evaluation model proposed in this paper are applied practically, and it is found that the accuracy and standardization of the stored medical and health big data are good, but the completeness, timeliness, interconnectivity and value are weak. In general, there is still some room for improvement. It can be improved from the aspects of data collection control, cross-platform data collaboration, and data value extraction in the future.

[Purpose/Significance] Use the advantages of information science theories and methods to promote the intelligent development of public opinion information research services in the process of public policy formulation in China. [Method/Process] The study analyzed the role of public opinion information in the whole process of public policy formulation, excavated practical difficulties, and introduced the RDJF cycle to put forward the optimization idea of public opinion information service model in the whole process of public policy formulation. [Results/Conclusion] The study constructs the public opinion information service framework for the whole process of public policy formulation, and proves the preciseness of the service framework by adjusting the policy formulation of national statutory holiday arrangements, providing a reference for optimizing the process of public policy formulation in China by using public opinion information.

[Purpose/Significance] The implementation of digital intelligence technology in intelligence work has enriched the participating elements of intelligence analysis and brought more professional requirements to intelligence personnel. The intelligence analysis under the perspective of components not only helps to standardize the work responsibilities of each element, but also can support the unified coordination of all elements under the standard process. [Methodology/Process] Firstly, the internal and external design of intelligence components was conceptualized and represented according to the software component model; secondly, the MVC design pattern and goal-centered process idea were introduced to standardize the combination principle and working mode of intelligence components; finally, the example development of intelligence analysis model was carried out with components as constituent units to demonstrate the flexibility and standardization of component-based analysis in terms of combination logic. [Results/Conclusion] Under the guidance of the combination principle and working pattern, intelligence components with different functions can be combined under the same level through the connection of external interfaces. The development example of intelligence analysis model based on the combination of components proves that intelligence component-based analysis not only ensures high-quality production of intelligence products, but also enhances the flexibility and standardization of intelligence analysis.

[Purpose/Meaning] Evaluating the influence of high-yield scholars is conducive to promote the enthusiasm of scholars, and can also provide references for superiors to introduce outstanding talents. The highly-productive scholars defined by Price Law are the influential backbone in a research field and play a crucial guiding role in scientific research. However, it is limited to judge the influence of scholars according to the single index of scientific research output. In addition to evaluate the absolute quantity of scholars' scientific research output, the quality of scientific research achievements shall also be considered within a reasonable evaluation method of scholars' influence, so as to carry out a multi-dimensional evaluation research on the comprehensive influence of scholars, including academic level. [Method/Process] In this paper, the study took three Nature Biotech sub-journals as examples, and their official websites were our data sources. On the basis of previous studies, the traditional index and Altmetrics index were selected then the relevant data were collected. The evaluation index system for highly-productive scholars was constructed separately from two dimensions which are scientific influence and social influence. Firstly, the indicators were screened by correlation analysis and other methods. Then factor analysis and principal component analysis were used to evaluate the scientific influence and social influence of highly-productive scholars, the correlation between the two dimensions was analyzed as well. Finally, the two-dimensional measurement results of the influence of highly-productive scholars were obtained. [Results/Conclusions] The results show that there is a large gap between the ranking of most scholars in the two influence dimensions, and the two dimensions show a strong positive correlation. Therefore, it is reasonable for this paper to combine the traditional index which illustrate scientific influence with the Altmetrics index which illustrate social influence to evaluate the comprehensive influence of highly-productive scholars. At the same time, by comparing the comprehensive influence of highly-productive scholars with different amounts of publications in this field, it is found that the "high output" of scientific research results do not completely mean "high quality", indicating that scholars should abandon the concept of putting the number of publications first, but to form a real team of high-quality prolific scholars to boost the development of the field.

[Purpose/Significance] As a key variable of innovation, geographical proximity attracts a lot of attention. Examining its impact on the speed of patent technology conversion helps improve the efficiency of patent conversion, and provides a reference for improving the technology conversion policy and optimizing the industrial cluster layout. [Method/Process] The study took the transferred and licensed patents in the industry of new energy automobile as the sample, examined the impact of geographical proximity on the speed of patent technology conversion with methods of inter group difference test, correlation analysis and regression analysis, by means of two types of indicators respectively, namely, spatial distance and traffic duration. [Results/Conclusion] The greater the space distance and land traffic duration between the two parties, the slower the patent technology conversion. The shortest traffic duration is of no impact. However, the situation has changed during the COVID-19 epidemic, with the positive effect of space proximity appearing. At this time, the smaller the space distance, the faster the conversion of patent technology.