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The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

The underlying software issue related to cited references is the capability of the software to identify the specific work cited by a reference, and associate it with the correct author and journal. This paper aims to investigate this issue and to discuss the latest editions of Web of Science (WoS) and Scopus.

In this paper the strengths and weaknesses of the Distinct Author Set feature of WoS and the Author Details feature of Scopus are discussed.

The paper reveals that these tools will have an increasingly important role in refining the process of disambiguating author (and journal) names in calculating their h‐index.

The paper provides useful information on software issues related to cited references and on the Distinct Author Set feature of WoS and the Author Details feature of Scopus.

The purpose of this paper is to report on the development and analysis of an internal bibliometric services workshop for subject librarians. Primary goals of the workshop were to create an opportunity for collegial knowledge and skill sharing, and to identify discipline specific gaps and future support requirements.

Two campus librarians who typically offer bibliometric support services used pre- and post-surveys to plan and assess the workshop for subject liaison librarians.

Subject librarians from across the university expressed interest in developing bibliometric support services. The 12 workshop participants (30 percent of subject librarians) support diverse areas including the humanities, social sciences, life sciences, education and outreach, and the school of business. Post-workshop survey respondents highlighted the contextualization of available measures and the appropriate application of metrics in different disciplines to be the most helpful topics covered. Finally, while the institution subscribes to several citation analysis databases, more familiarity with Google Scholar citations was requested to address user needs and preferences across the various disciplines. Most participants expressed interest in attending additional workshops.

This study showcases the experience of campus librarians working together across academic schools and disciplines to respond to the increasing demand for bibliometric and scholarly impact support services. While services such as citation analysis have typically been siloed in specific job descriptions or subject areas within the library, these are service areas that can benefit from internal library-collaboration opportunities and knowledge sharing.

To propose improvements to the identification of authors' names in digital repositories.

Analysis of current name authorities in digital resources, particularly in digital repositories, and analysis of some features of existing repository applications.

This paper finds that the variations of authors' names have negatively affected the retrieval capability of digital repositories. Two possible solutions include using composite identifiers that combine author name, publication date, and author affiliation, and also asking authors to input the variants of their name, if any, at the time of depositing articles.

This is the first time that the approach of authors self‐depositing their name variations is proposed. This approach will be able to reduce confusions in name identification.

Academic contention occurs when research evidence is amenable to more than one interpretation. China has a long tradition of Shang Que (商榷), in which authors argue for their preferred interpretation. The modern form of this tradition is the Shang Que article, which often takes the form of research papers in Chinese-language journals and which tends to be question-oriented. Shang Que articles usually take the views of a particular author or article as the focus of independent and complete criticism by another, independent, academic. This paper explains the role of Shang Que articles in Chinese scholarship and their influence on international academia.

A bibliometric analysis was used to explore the characteristics and evolution of Chinese Shang Que articles using 30,577 articles published between 1979 and 2018. Microsoft Excel and Gephi were used for data analysis and visualization.

Findings suggest a decline in the number of Shang Que articles and an increase in the number of co-authors. Shang Que articles remained particularly prominent in Philosophy and Humanities and Social Sciences, where they focused on local issues such as classical Chinese, the Sinicization of Marxism and Chinese literature. This suggests that the number of Shang Que articles is related to the degree of internationalization of a research field.

Shang Que articles, which have been influenced by academic paradigms in English, are a fusion of China's Shang Que tradition and of the modern academic system. Through considering Shang Que articles, this paper explores the benefits of local academic traditions in non-English-speaking cultures.

This study aims to apply some concepts of actuarial statistics to the authorship of Iranian ISI papers in the field of chemistry based on Price’s model. The study determines scientific birth rate, death rate, infant mortality rate, natural increase rate and life expectancy.

Price maintained that authors in each given period in any field fall into four categories including newcomers, transients, continuants and terminators. He suggested that actuarial statistics could be applied to authorship to calculate death rate and birth rate in scientific fields. A total 25,573 papers written by 59,661 Iranian chemistry authors between 1973 and 2012 were downloaded from Web of Science (WoS) and were subjected to statistical analysis.

The average birth rate was 66.7 per cent, the average death rate was 19.4 per cent, infant mortality rate was 51.2 per cent, average natural increase was 47.3 per cent, the average life expectancy was 1.98 years and the longest scientific age was 22 years. The results show that although a large number of people start their scientific activity, the number of those who terminate their activity in the same year as they start (infant mortality rate) is also large and little continuity exists in the publishing activities of Iranian chemists.

The findings have implications for the planning of human resources in science. They could help maintain a stable scientific labor force and decide for instance whether a larger number of scientists should be trained and hired, or the barriers should be removed so the existing scientists can work for more years. The limitation is that the study is restricted to ISI articles, although they are not the only kind of scientific output.

This is the first study of its kind on Iranian scientific output. It shows that the overall labor force in the field of chemistry in Iran was not satisfactory, as the majority of authors in each period are transients. There is a need for better planning for the labor force.

The purpose of this paper is to collect and understand the nature of real cases of author name variants that have often appeared in bibliographic digital libraries (DLs) as a case study of the name authority control problem in DLs.

To find a sample of name variants across DLs (e.g. DBLP and ACM) and in a single DL (e.g. ACM), the approach is based on two bipartite matching algorithms: Maximum Weighted Bipartite Matching and Maximum Cardinality Bipartite Matching.

First, the authors validated the effectiveness and efficiency of the bipartite matching algorithms. The authors also studied the nature of real cases of author name variants that had been found across DLs (e.g. ACM, CiteSeer and DBLP) and in a single DL.

To the best of the authors knowledge, there is less research effort to understand the nature of author name variants shown in DLs. A thorough analysis can help focus research effort on real problems that arise when the authors perform duplicate detection methods.

The aim of this study is to present a novel approach based on semantic fingerprinting and a clustering algorithm called density-based spatial clustering of applications with noise (DBSCAN), which can be used to convert investor records into 128-bit semantic fingerprints. Inventor disambiguation is a method used to discover a unique set of underlying inventors and map a set of patents to their corresponding inventors. Resolving the ambiguities between inventors is necessary to improve the quality of the patent database and to ensure accurate entity-level analysis. Most existing methods are based on machine learning and, while they often show good performance, this comes at the cost of time, computational power and storage space.

Using DBSCAN, the meta and textual data in inventor records are converted into 128-bit semantic fingerprints. However, rather than using a string comparison or cosine similarity to calculate the distance between pair-wise fingerprint records, a binary number comparison function was used in DBSCAN. DBSCAN then clusters the inventor records based on this distance to disambiguate inventor names.

Experiments conducted on the PatentsView campaign database of the United States Patent and Trademark Office show that this method disambiguates inventor names with recall greater than 99 per cent in less time and with substantially smaller storage requirement.

A better semantic fingerprint algorithm and a better distance function may improve precision. Setting of different clustering parameters for each block or other clustering algorithms will be considered to improve the accuracy of the disambiguation results even further.

Compared with the existing methods, the proposed method does not rely on feature selection and complex feature comparison computation. Most importantly, running time and storage requirements are drastically reduced.

The purpose of this paper is to support the use of unique identifiers for the authors of scientific publications. This, the authors believe, aligns with the views of many others, as it would solve the problem of author disambiguation. If every researcher had a unique identifier, there would be significant opportunities to provide even more services. These extensions are proposed in this paper.

The authors discuss the bibliographic services that are currently available. This leads to a discussion of how these services could be developed and extended.

The authors suggest a number of ways that a unique identifier for scientific authors could support many other areas of importance to the scientific community. This will provide a much more robust system that provides a much richer and more easily maintained, scientific environment.

The scientific community lags behind most other communities with regard to the way it identifies individuals. Even if the current vision for a unique identifier for authors was to become more widespread, there would still be many areas where the community could improve its operations. This viewpoint paper suggests some of these, along with a financial model that could underpin the functionality.

The purpose of this paper is to identify embedded communities among Medical Ethics scholars in France based on their position and strength of association in the social networks they form.

The author constructed a co-authorship network by linking two authors if they co-authored a paper. Once the co-authorship network was constructed, the author investigated the entire network quantitatively using standard research methods known as social network analysis. The author’s mechanism of community detection was via identification, i.e. communities were user-defined based on topological analysis.

The study identified that communities formed by trust (bonding or repeat connections) or by prestige (connection of well-connected scholars with those that are already well-connected) overlap each other, suggesting that trust and prestige may go hand in hand in sustaining communities. Structural holes within trust networks indicated that some actors played more of a broker role than did other actors.

The study uses Web of Science field based category to extract data. Although thorough cleaning of data has been performed, author disambiguation over a three decade period remains a limitation.

Although there have been numerous studies on mapping co-authorship networks, there has been limited work investigating the underlying communities formed by author associations. The results of this study should be of immense benefit to those studying the science of science and S&T policy.