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Under the background of open science, this paper integrates altmetrics data and combines multiple evaluation methods to analyze and evaluate the indicators' characteristics of discourse leading for academic journals, which is of great significance to enrich and improve the evaluation theory and indicator system of academic journals.

This paper obtained 795,631 citations and 10.3 million altmetrics indicators data for 126,424 published papers from 151 medicine, general and internal academic journals. In this paper, descriptive statistical analysis and distribution rules of evaluation indicators are first carried out at the macro level. The distribution characteristics of evaluation indicators under different international collaboration conditions are analyzed at the micro level. Second, according to the characteristics and connotation of the evaluation indicators, the evaluation indicator system is constructed. Third, correlation analysis, factor analysis, entropy weight method and TOPSIS method are adopted to evaluate and analyze the discourse leading in medicine, general and internal academic journals by integrating altmetrics. At the same time, this paper verifies the reliability of the evaluation results.

Six features of discourse leading integrated with altmetrics indicators are obtained. In the era of open science, online academic exchanges are becoming more and more popular. The evaluation activities based on altmetrics have fine-grained and procedural advantages. It is feasible and necessary to integrate altmetrics indicators and combine the advantages of multiple methods to evaluate the academic journals' discourse leading of which are in a diversified academic ecosystem.

This paper uses descriptive statistical analysis to analyze the distribution characteristics and distribution rules of discourse leading indicators of academic journals and to explore the availability of altmetrics indicators and the effectiveness of constructing an evaluation system. Then, combining the advantages of multiple evaluation methods, The author integrates altmetrics indicators to comprehensively evaluate the discourse leading of academic journals and verify the reliability of the evaluation results. This paper aims to provide references for enriching and improving the evaluation theory and indicator system of academic journals.

This paper aims to analyze the relationships between discourse leading indicators and citations from perspectives of integrating altmetrics indicators and tries to provide references for comprehending the quantitative indicators of scientific communication in the era of open science, constructing the evaluation indicator system of the discourse leading for academic journals and then improving the discourse leading of academic journals.

Based on the theory of communication and the new pattern of scientific communication, this paper explores the formation process of academic journals' discourse leading. This paper obtains 874,119 citations and 6,378,843 altmetrics indicators data from 65 international multidisciplinary academic journals. The relationships between indicators of discourse leading (altmetrics) and citations are studied by using descriptive statistical analysis, correlation analysis, principal component analysis, negative binomial regression analysis and marginal effects analysis. Meanwhile, the connotation and essential characteristics of the indicators, the strength and influence of the relationships are further analyzed and explored. It is proposed that academic journals' discourse leading is composed of news discourse leading, social media discourse leading, peer review discourse leading, encyclopedic discourse leading, video discourse leading and policy discourse leading.

It is discovered that the 15 altmetrics indicators data have a low degree of centralization to the center and a high degree of polarization dispersion overall; their distribution patterns do not follow the normal distributions, and their distributions have the characteristics of long-tailed right-peaked curves. Overall, 15 indicators show positive correlations and wide gaps exist in the number of mentions and coverage. The academic journals' discourse leading significantly affects total cites. When altmetrics indicators of international mainstream academic and social media platforms are used to explore the connotation and characteristics of academic journals' discourse leading, the influence or contribution of social media discourse, news discourse, video discourse, policy discourse, peer review discourse and encyclopedia discourse on the citations decreases in turn.

This study is innovative from the academic journal level to analyze the deep relationships between altmetrics indicators and citations from the perspective of correlation. First, this paper explores the formation process of academic journals' discourse leading. Second, this paper integrates altmetrics indicators to study the correlation between discourse leading indicators and citations. This study will help to enrich and improve basic theoretical issues and indicators’ composition, provide theoretical support for the construction of the discourse leading evaluation system for academic journals and provide ideas for the evaluation practice activities.

This paper aims to conduct a comprehensive analysis to evaluate the current situation of journals, examine the factors that influence their development, and establish an evaluation index system and model. The objective is to enhance the theory and methodologies used for journal evaluation and provide guidance for their positive development.

This study uses empirical data from economics journals to analyse their evaluation dimensions, methods, index system and evaluation framework. This study then assigns weights to journal data using single and combined evaluations in three dimensions: influence, communication and novelty. It calculates several evaluation metrics, including the explanation rate, information entropy value, difference coefficient and novelty degree. Finally, this study applies the concept of fuzzy mathematics to measure the final results.

The use of affiliation degree and fuzzy Borda number can synthesize ranking and score differences among evaluation methods. It combines internal objective information and improves model accuracy. The novelty of journal topics positively correlates with both the journal impact factor and social media mentions. In addition, journal communication power indicators compensate for the shortcomings of traditional citation analysis. Finally, the three-dimensional representative evaluation index serves as a reminder to academic journals to avoid the vortex of the Matthew effect.

This paper proposes a journal evaluation model comprising academic influence, communication power and novelty dimensions. It uses fuzzy Borda evaluation to address issues related to the weighing of single evaluation methods. This study also analyses the relationship of the three dimensions and offers insights for journal development in the new media era.

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

The research in this paper aims to investigate the development of Library and Information Science in Chinese universities. Specifically, it focuses on understanding the spatial and temporal aspects of subject knowledge output and providing a more comprehensive explanation of the imbalance in subject research.

This study applies the bibliometric method to analyze 131,112 papers published by 51 universities in mainland China from 1977 to 2021, as recorded in the Chinese Social Sciences Citation Index (CSSCI). The study classifies the evolution trends of the discipline and quantifies the published article data of the universities using the index of published articles. Additionally, it examines the development status, structural situation, influencing factors and prospects of universities in different categories and regions.

The field of Library and Information Science is gaining momentum in Chinese universities, but there are significant differences in its development. While the relative gap among universities in a regional context is diminishing, the absolute gap in the category perspective is increasing. The development of Library and Information Science is influenced by various factors, including the academic environment, geographical position, scientific research projects and academic traditions. The uneven development of the discipline is maintained in the short term.

This paper proposes a new quantitative index of discipline development, the university publication index. This index allows for an examination of the temporal and spatial trends of discipline development using domestic universities as the subject of research. The paper presents an overview of discipline development through four aspects: academic participation practice, discipline governance mechanisms, education and teaching systems and discourse construction within the discipline. The theoretical support provided by this study can help facilitate innovative development in the discipline.

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

The main objective of the present study is to determine the role of citation-based metrics (PageRank and HITS’ authority and hub scores) and non-citation metrics (Goodreads readers, reviews and ratings, textbook edition counts) in predicting educational ranks of textbooks.

The rankings of 1869 academic textbooks of various disciplines indexed in Scopus were extracted from the Open Syllabus Project (OSP) and compared with normalized counts of Scopus citations, scores of PageRank, authority and hub (HITS) in Scopus book-to-book citation network, Goodreads ratings and reviews, review sentiment scores and WorldCat book editions.

Prediction of the educational rank of scholarly syllabus books ranged from 32% in technology to 68% in philosophy, psychology and religion. WorldCat editions in social sciences, medicine and technology, Goodreads ratings in humanities, and book-citation-network authority scores in law and political science accounted for the strongest predictions of the educational score. Thus, each indicator of editions, Goodreads ratings, and book citation authority score alone can be used to show the rank of the academic textbooks, and if used in combination, they will help explain the educational uptake of books even better.

This is the first study examining the role of citation indicators, Goodreads readers, reviews and ratings in predicting the OSP rank of academic books.

In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks.

This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient.

The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly.

The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community.

The rise of the metaverse has brought profound changes to the economic and social operation models and injected new vitality into academic research. Although a large number of studies have emerged, there are few quantitative analyses of development frontiers and trends.

From a bibliometric perspective, this paper selects 183 pieces of metaverse-related literature in the WoS core database since 2000 as the object of analysis. This paper sums up the characteristics of the literature using the methods of descriptive statistical analysis, keywords analysis, thematic evolution analysis and summarizes the core themes and the laws of metaverse development in each stage.

The digital economy vision brought by the metaverse has led to an increasing number of researchers and achievements in this field. But the depth and breadth of research are still insufficient and unevenly distributed in the region, and the cross-fertilization fields need to be expanded. From the industry's point of view, VR games represented by Second Life and My World have contributed to the popularity of the metaverse. As technology progresses, the research hotspots in the field of metaverse gradually develop from conceptual research to artificial intelligence, blockchain, NFT and other technical applications. However, academic research has not yet caught up with the industry's pace and stays more in the concept discussion and preliminary application stage.

A systematic overview of the current status, knowledge structure and hot issues of metaverse research is shown, which provides a thematic axis for this field, enriches and improves the quantitative analysis of its literature and provides a clear picture for researchers to continuously promote the development of this field. At the same time, it is necessary to warn that technological development is a double-edged sword. The process of metaverse development should return to rationality, respect the laws of its development and guarantee the healthy development of the metaverse by strengthening legal regulation and the ethical review of science and technology.

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications.

This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns.

The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication.

Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.