[Purpose/Significance] In order to reveal the development path and characteristics of information science at home and abroad in a more comprehensive and detailed way, so as to help scholars have a deeper understanding of the development of the field from a more macro perspective. [Method/Process] This paper took the representative core journal papers in the field of information science at home and abroad as data sources, and adopted methods such as co-citation analysis, word frequency method and knowledge graph to visually present the research fronts and evolution trends in the field of information science at home and abroad. [Results/Conclusion] Firstly, the comparison reveals that there are both similarities and differences in the research front topics of information science at home and abroad.Secondly, the classical research front evolution path in the field of domestic information science include the evolution path focusing on library information service and the evolution path focusing on metrology and information visualization, while the classic research front evolution path in foreign countries is the evolution path focusing on user perception and user behavior.The fundamental reason for the difference in the performance of typical research front evolution paths at home and abroad lies in the different origins, development backgrounds and research paradigms of information science at home and abroad.

[Purpose/Significance] To explore the construction strategy of digital humanities industry alliance, plan its future development path, and broaden the research ideas in the field of digital humanities.The transformation efficiency of digital humanities from digital humanities knowledge to productivity to economic benefits will be strengthened. [Method/Process] From the perspective of knowledge flow, this paper clarified the concept of digital humanity industry, analyzed the knowledge flow path of digital humanity industry, and explored the construction strategy and development path of digital humanity industry alliance. [Result/Conclusion] Define the concepts of digital humanities products and the digital humanities industry, analyze the knowledge flow paths in the digital humanities industry, construct a model of the digital humanities industry alliance from the perspective of knowledge flow, propose construction strategies for the key elements of knowledge involving enterprises, higher education institutions and research organizations, governments, and industry associations/organizations, etc., and plan a three-step development path that encompasses"Looking to the Future", "Focusing on the Present", and"Overtaking on a Bend".

[Purpose/Significance] Open innovation community is an important place for users to share knowledge.It is crucial for managers to clarify the roles and synergies of knowledge sharing among different user groups to improve the level of knowledge sharing in the community. [Methods/Process] This paper firstly located the leading users, core users and long tail users through K-means clustering, and then analyzed the role and synergies of the three user groups through grounded theory. [Result/Conclusion] There are three main findings in the research.First, three types of user groups experience four stages of knowledge integration, knowledge production, knowledge dissemination and knowledge application.Secondly, three types of user groups play different roles in the process of knowledge sharing, such as knowledge miner and producer, knowledge integrator and diffuser, knowledge absorber and practitioner.Third, the three types of users influence each other and cooperate in the process of knowledge sharing.

[Purpose/Significance] The study applies the social network analysis method to the research on the characteristics and laws of scientific data citations can intuitively present the complex network structure of data citations, and taps the deeper value of data citations. [Method/Process] The study constructed a GEO data co-citation network model by analyzing the citation characteristics of scientific data, and analyzed the overall evolution of the network, core individuals, and community structures. [Result/conclusion] The research results show that the degree and degree distribution space of the GEO data co-citation network are significantly different, the average path length is shorter and the aggregation coefficient is larger, the core individual advantages in the network are obvious, the community structure is stable and the characteristics are prominent, and the community The connection between them is gradually strengthened.

[Purpose/Significance] The study aims to investigate the mechanisms of the privacy paradox and the differences in privacy protective behavior among individuals.The findings would offer theoretical references contributing to the advancement of platform privacy management. [Method/Process] Based on the Promotion Motivation Theory(PMT), this study introduced privacy protection fatigue as a mediator and self-efficacy as a moderator, and initiated a large online survey in 16 cities across China(N=4 800). [Result/Conclusion] The results reveal that privacy protection fatigue negatively mediates the positive relationship between privacy invasion experience and privacy protection intention.Additionally, self efficacy has a positive moderating effect(weakening effect)on the inverted U-shaped relationship between privacy invasion experience and privacy protection fatigue.Meanwhile, self efficacy also has a negative moderating effect(weakening effect)on the positive relationship between privacy invasion experience and privacy protection intention.

[Purpose/Significance] Based on the information foraging theory, this study aims to analyze the internal mechanism of consumer online review search behavior of review software. [Method/Process] Based on information foraging theory, this study firstly constructed a behavioral model of online review search by using information clues, patch model and menu model.In addition, the study adopted the questionnaire as the research method and collected 352 valid samples.Finally, the study used the SEM to analyze the data and then test the theoretical model. [Result/Conclusion] Four types of information clues, including the quality of reviews' contents, the variety of reviews, the sentiment of reviews and the credibility of reviewers, would positively and significantly affect consumers' perception of patch benefit, and then positively affect consumer online review search behavior.In addition, the sentiment of reviews would also directly and positively affect consumers' online review search behavior.This study, in theory, deeply reveals the internal mechanism of consumer online review search behavior, and extends the research context and boundary of information foraging theory.In practice, some suggestions are provided to optimize the function of review software and guide consumers to search online reviews effectively.

[Purpose/Significance] From the dual perspectives of user similarity calculation and user feedback, high-quality user recommendation is conducive to improving the personalized recommendation level of the network knowledge community. [Method/Process] Firstly, the paper collected and analyzed users' attributes data based on crawler tools and python packages to calculate the comprehensive similarity between user pairs in terms of background, social relationships, and blog information; then calculated the users' core scores and formed a recommendation list based on the similarity matrix and core user ranking; finally, introducing a user feedback mechanism and determine the best top-k friends based on positive and negative feedback results of the user. [Result/Conclusion] The friend recommendation model incorporating user feedback can improve the quality of recommended users, effectively improve the level of friend recommendation, and also verify that friend recommendation is a gradual repair process.

[Purpose/Significance] Scientific papers play a crucial role in the transmission and exchange of knowledge within academia.The evaluation of scientific paper reviews serves as an indicator of the knowledge value contained in these papers.Efficient and accurate prediction of scientific paper review classifications can enable swift assessment of their worth, thereby expediting the dissemination process for valuable knowledge. [Method/Process] This study delved into an automatic review classification method within open peer review systems.By harnessing semantic information extracted from scientific papers and expert ratings obtained during open peer reviews, the study constructed text representations and classification models.Traditional machine-learning approaches and deep-learning techniques were employed to generate automatic review classification results. [Result/Conclusion] Experimental findings demonstrate that integrating semantic information with rating data led to more effective review classification models compared to relying solely on mean ratings for judgment purposes.Among the various models tested, the quality review classification model based on SCIBERT with the input of rating+mean achieved the highest accuracy at 90.17%.The proposed automatic review classification method demonstrated usability and high accuracy, offering valuable assistance to journal editors in swiftly screening potential scientific papers and contributing to intelligent advancements in the field of scientific paper reviewing.

[Purpose/Significance] The group polarization of network public opinion in emergencies is the most harmful result of public opinion evolution.The group polarization risk assessment of network public opinion in emergencies is the starting link of risk identification and guidance strategies, and is an important part of group polarization social risk management. [Method/Process] Based on the conceptual model of group polarization risk assessment, this paper constructed a risk assessment index system, and designed a classification assessment method for the group polarization risk level of network public opinion in emergencies based on AHPSortⅡ.Finally, it conducted an empirical study through a case. [Result/Conclusion] The group polarization risk assessment method of emergency network public opinion constructed in this paper can realize the classification and calculation of group polarization risk grade, which has certain accuracy and rationality, and provides theoretical support for the management department to accurately grasp the occurrence, development status and trend of group polarization risk, and realizes scientific classification of risk.

[Purpose/Significance] Refutation is widely regarded as a primary method for reducing the impact of false information. This study investigates the influence of various elements of social media refutation on the Continuous Influence Effect (CIE) of misinformation. Furthermore, it aims to identify key factors that enhance CIE, refine theories such as knowledge correction, and mitigate the impact of an"information pandemic". [Method/Process] Based on the Knowledge Correction Theory as the foundational model, the study conducted a retrospective survey using a questionnaire to investigate social media users and constructed a model of the factors influencing the Continuous Influence Effect (CIE) of users from two dimensions: individual factors and refutation information factors.To validate the reliability of this model, it employed Smart PLS software for analysis. [Result/Conclusion] The impact of online refutation information on the Continuous Influence Effect (CIE) of social media users is primarily influenced by seven factors: the frequency of refutation information, refutation response speed, individual self-confidence level, comprehensiveness of refutation information, source of refutation information, directed reasoning motivation, and cognitive ability regarding refutation information content. These seven factors collectively regulate the entire process of knowledge correction for social media users. Among these factors, the source of refutation information, directed reasoning motivation, and cognitive ability regarding refutation information content play a relatively dominant role in users' ability to mitigate the CIE.

[Purpose/Significance] Constructing a machine learning-based patent value assessment method is constructed to quickly identify the actual costs of a large number of patents and predict their value ranges, which provides a new research idea for patent value assessment as well as a reference for the pricing of patent transfer and transformation. [Method/Process] Using data from Innography and Incopat databases, multiple indicator patent data in the field of "new energy vehicles" were downloaded. The study extracted factors influencing patent costs and patent value. Subsequently, patent data training sets and prediction sets were formed. An AutoGluon machine learning classification algorithm was established, and the Innography patent data training set containing cost data was imported into the model for training. The trained model was then used to predict costs for the Incopat patent data prediction set. Finally, employing the cost approach and combining it with the patent value index proposed in this study, the results were calculated to estimate the price range. [Results/Conclusion] Through empirical analysis and result verification, it was evident that the machine learning-based cost approach for patent valuation constructed in this study demonstrates a certain level of effectiveness in predicting the value range of patents. This provided a reference for promoting the deepening of patent value assessment research and the development of pricing practice in patent transfer and transformation.

[Purpose/Significance] This paper investigates and analyzes the open research data policy system issued by world-class universities, in order to put forward policy suggestions for domestic research institutions to formulate and improve their open research data policy system. [Method/Process] This paper firstly investigated the open research data policy system issued by world-class universities, secondly summarized the policy types and related policies and regulations involved in their open research data policy system, then analyzed the policy content elements related to open research data that should be covered by each policy type, and finally put forward policy suggestions for domestic research institutions to formulate and improve their open research data policy system. [Result/Conclusion] It is suggested that domestic research institutions should make reference to the advanced policy practices of world-class universities, and formulate their open research data policy system covering personal data protection, research records management, research integrity management, research ethics governance, intellectual property protection, data security management and other related policies as soon as possible, and support the coordinated management of research data, primary materials and research records at the policy formulation level, with a view to ensure compliance with various relevant policies and regulations throughout the entire lifecycle of research data, which have been continuously adjusted in recent years, and to pay attention to the policy synergy issues between open research data policies formulated by research institutions and other stakeholders such as funding agencies, publishers and data repositories.

[Purpose/Significance] The cross integration of science and technology is an important growth point for cutting-edge innovation breakthroughs. By systematically reviewing and summarizing research achievements in interdisciplinary fields both domestically and internationally, the paper aims to provide reference for future research in this field. [Method/Process] Based on three types of cross field approaches, including internal cross field within the scientific field, internal cross field within the technical field, and cross field between the scientific and technological fields, this study aimed to clarify the conceptual relationships and connotations of cross field approaches. From the perspectives of econometrics and text mining, the paper provided a detailed explanation of the correlation measurement methods for cross disciplinary approaches. [Result/Conclusion] Based on existing research, the paper provides the conceptual relationships and correlation measurement framework for cross field research, and summarize the future development direction of this field from three aspects. First, cross research based on massive, multi-source, and heterogeneous data such as scientific reports, monographs, standards, papers, and patents. Second, comprehensive global analysis of three types of cross domain. Third, detection of cutting-edge innovation directions in cross domain.