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Collaboration is an important way for scientific research. It attracts a large number of researchers, and forms a series of measurement evaluation indicators. The purpose of this study further enriches the evaluation system of collaboration and provides new indicators to measure collaboration ability at author level in order to identify the most appropriate potential partners.

The papers published during the period 2006-2015 and collected from Web of Science Core Collection in library and information science (LIS) are regarded as data source. And it defines and measures the collaborative rate, collaborative breadth and collaborative depth at author level.

The authors’ research shows that collaboration is an important way in the scientific research activities in LIS. Unfortunately, most author’s collaborative breadth and the collaborative depth are lower than mean. Therefore, the author’s scope and stability of collaboration is further strengthened in future. Authors can identify the most appropriate potential partners according to author’s research purpose and the region of the collaborative breadth – the collaborative depth.

It further enriches the evaluation system of collaboration and provides new indicators to evaluate collaboration ability at author level. Authors can identify the most appropriate potential partners according to author’s collaboration ability.

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.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

The purpose of this paper is to generalize the teaching characteristics of some typical colleges in China which offer Informetrics courses, and to propose useful suggestions for the course construction of Informetrics through empirical investigation.

The statuses of Informetrics curriculum education of the top ten universities in Library and Information Science and Archives Management in Chinese mainland as well as Fu Jen Catholic University in Taiwan have been investigated and analyzed through a network survey and a telephone survey. Wuhan University and Fu Jen Catholic University are considered as the typical examples.

The educational development of Informetrics in China has gone through three stages: the initial stage, the developing stage and the improving stage. Based on the empirical investigation and analysis, some meaningful conclusions are drawn concerning the education system, teaching objectives, teaching contents and teaching methods of Informetrics courses.

This paper provides curricular information about Informetrics courses in China.

Academic conferences play a crucial role in fostering scholarly exchanges and discussions among core members, thereby shaping the core performance of these events. Understanding the contributions of scholars in academic conferences is essential for advancing the goals and development of such events. This paper aims to discuss the aforementioned idea.

This paper proposes a comprehensive measurement method for measuring scholars' academic activeness in academic conferences. Based on the essence of academic activeness, a measurement model is constructed, comprising the breadth of academic activeness using the RFM model and the depth of academic activeness using the ATM model. Additionally, effective categories of scholars are derived from the model, facilitating the identification of valuable scholars in academic conferences.

Empirical evidence from ASIS&T conference records over the past 20 years demonstrates that the proposed measurement indicators have better coverage compared to traditional evaluation indicators, thus complementing existing scholar evaluation indictators. Furthermore, the academic activeness measurement model presented in this paper exhibits good efficacy in identifying important value and active scholars.

This paper pays attention to the activeness of scholars in academic conferences. It broadens the evaluation of academic conferences and scholars and supplements the evaluation indicators of academic influence.

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.

The influencing factors of academic papers have always been the focus of attention in the field of Scientometrics. Exploring the influencing factors of altmetrics indicators and traditional literature indicators on academic papers is beneficial to better explore the potential significance and value of academic papers in the evaluation of scientific research. The paper aims to discuss these issues.

Based on the latest JCR citation report, this paper selects 22 academic journals in the JIF Quartile Q1 journal of Information Science and Library Science, and then obtains the evaluation data of these journal papers from WOS database and Altmetric.com. This paper uses literature measurement, correlation analysis and regression analysis to explore the influencing factors of the paper.

The results show that the original influencing factors of academic papers have a significant impact on secondary influencing factors. What is more obvious is that the number of references (nr) presents a significant positive correlation with the total number of times (Z9), the number of uses (U1) and (U2).

This paper combines traditional literature indicators with Altmetrics indicators to study the influencing factors through primary influencing factors and secondary influencing factors. Through research, it denies the phenomenon that academic circles have published academic papers in the world in recent years to overemphasize certain factors to improve the influence of the paper.

The purpose of this paper is to introduce altmetric indicators and combine with traditional citation indicators to comprehensively evaluate the impact of academic journals from the perspective of multidimensional and multi-indicator fusion.

The authors take international multidisciplinary journals as an example, combining 14 traditional citation indicators of academic journals and introducing 14 altmetric indicators to build a comprehensive evaluation model of the impact of academic journals (academic impact and societal impact). At the same time, the authors systematically construct a journal evaluation indicator system from three dimensions. Then, the indicators data of three dimensions are evaluated by normalized processing, correlation analysis, reliability and validity analysis, PCA and factor analysis.

Two-dimensional and three-dimensional analyses can exactly provide some useful information for academic journals’ location in the respective coordinate systems. There are strong positive correlations among the measured indicators in the three dimensions, and each indicator has a significant consistency between whole and internal. The correlation coefficient between FD1 and FD2 is 0.888 with a strong positive correlation. It shows that the traditional citation indicators provided by WoS and Scopus database are highly consistent, and they are comparable and alternative in evaluating the academic impact of journals. The correlation coefficients of FD1, FD2 with FD3 are 0.831 and 0.798. There are strong positive correlations among them, which indicate that the evaluation of journals’ societal impact based on altmetrics indicator can be considered as a potential supplement to academic impact evaluation based on citation and to reflect the multidimensional nature of journals impact in an immediate way.

Multidimensional and multi-indicator perspective evaluation can provide references for the selection of impact evaluation indicators and model optimization of academic journals, and also provide new ideas for improving the status of the impact evaluation of academic journals.

The purpose of this paper is to further explore the co-citation and bibliographic-coupling relationship among the core authors in the field of Chinese information science (IS), to expose research activity and author impact, and to make induction analyses about Chinese IS research patterns and theme evolution.

The research data include 8,567 papers and 70,947 cited articles in the IS field indexed by Chinese Social Sciences Citation Index from 2000 to 2009. Author co-citation analysis, author bibliographic-coupling analysis, social network analysis, and factor analysis were combined to explore co-citation and bibliographic-coupling relationships and to identify research groups and subjects.

Scholars with greatest impact are different from the most active scholars of Chinese IS; there is no uniform impact pattern forming since authors’ impact subjects are scattered and not steady; while authors’ research activities present higher independence and concentration, there is still no steady research pattern due to no deep research existing. Furthermore, Chinese IS studies can be delineated by: foundation or extension. The research subjects of these two parts, as well as their corresponding/contributing authors, are different under different views. The general research status of core authors is concentrated, while their impact is broad.

The combined use of some related methods could enrich the development and methodology research of the discipline, and the results establish a reference point on the development of IS research.