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In the COVID-19 pandemic, it was much more critical for many life science researchers to rapidly disseminate research results—so they used preprints as upstream publication opportunities. This was rather new to the life sciences where preprint servers had only appeared as early as 2013. With a mixed-methods-study we examined this development and investigated whether preprint posting is a temporary phenomenon or the beginning of a cultural shift in publishing behavior in the life sciences. First, we conducted a survey of researchers who have posted COVID-19 related preprints. We investigated experiences with posting preprints during the COVID-19 pandemic, motivations for and concerns about posting preprints, the role of research institutions or funders, and the future of preprint publishing. Answers were grouped to compare differences between respondents' gender, career stage, region of origin (global south or global north) and experience with posting preprints before and during the COVID-19 pandemic. We further analyzed eight popular preprint repositories regarding the number of posted preprints and preprint characteristics, such as the number of authors and citations. Interestingly, survey and preprint server analysis have presented different, if not contradicting results: While the majority of surveyed researchers was willing to continue posting preprints, the numbers of preprints published, especially on servers for the life sciences, have stagnated or declined. Also, while certain preprints garnered substantial citations during the COVID-19 pandemic, this has not resulted in a significant shift in researchers' publishing behavior, and the posting of preprints has not become a routine. We concluded that the sustainability of preprint publishing practices is more strongly influenced by disciplinary norms and practices than by external shocks as the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing surname initial techniques in academic publications and their impact on citation counts. Focusing on the disciplines of Economics, Psychology, Political Science, and Sociology, we utilized data from the top 500 universities listed in the Shanghai List. Examining 70.377 academic publications from 2.278 academics published between 2011 and 2020, the study reveals that alphabetical ordering is more prevalent in Economics and Political Science. Academics with surnames placed at the beginning of the alphabet in these fields experience increased visibility and recognition. Conversely, those with surnames placed at the end of the alphabet face disadvantages and often employ strategies such as changing surname initials, using hyphenated surnames, or adding prefixes to improve their positioning in the author list of the article. These strategies, influenced by factors like the number of authors, country of origin, gender and whether the advantage is gained or not in positioning of author list, help mitigate the unfairness caused by alphabetization and positively contribute to authors' citation statistics. [ABSTRACT FROM AUTHOR]

This study outlines the intellectual structure of Library and Information Science in terms of the venues with RefCit2vec, an embedding method inspired by word2vec. The reference lists or cited-by lists of 62,077 articles in 35 venues (journals and proceedings) between 1928 and 2022 are converted into real number vectors by four independent models of RefCit2vec. The document similarities measured by the two models of RefCit2vec exhibit moderate correlations with bibliographical coupling metrics. In contrast, the similarities from the other two models moderately or strongly correlate with co-citation metrics. Each venue is represented by its centroid, the average vector of its constituent documents. By applying hierarchical agglomerative clustering on the venue centroids, 69% of venues robustly emerge in 6 out of 8 clusters. Four clusters consistently form the library-related branch. The bibliometrics/scientometrics branch contains only 1 cluster, whereas the information-related branch contains 3 clusters. 43% of venues are in six subgroups of consistent tree structures. An article is defined as SCIM-alike for it is closer to the SCIM centroid than half of SCIM articles are. 10% of JASIST articles are SCIM-alike upon their reference lists, and 5% of JASIST articles are SCIM-alike in terms of their cited-by lists. The percentage of SCIM-alike articles in JASIST hiked above the average between 2008 and 2018 but has dropped below the average since 2019. As we demonstrate the dynamics in LIS, citation embedding methods like RefCit2vec can incorporate citation-based, text-based, or authorship features to contribute to varied scenarios in investigating or exploring research fronts and scientific knowledge transfer. [ABSTRACT FROM AUTHOR]

Many claims have been made in the past that Management and Organization Studies (MOS) is becoming increasingly fragmented, and that this fragmentation is causing it to drift into self-reference and irrelevance. Despite the weight of this claim, it has not yet been subjected to a systematic empirical test. This paper addresses this research gap using the tribalization approach and diachronic co-citation analyses. Based on 22,430 papers published in 14 MOS journals between 1980 and 2019, we calculate local and global centrality measures and the flow of cited articles between co-citation communities over time. In addition, we use a node-removal strategy to test whether only ritualized citations ensure MOS cohesion. Rather than tribalization, our results suggest a center–periphery structure. Furthermore, more peripheral papers are integrated into the central co-citation communities, but the lion's share of the flow of cited papers occurs over time to only a small number of large clusters. An increase of fragmentation and crowding-out of smaller clusters in MOS in seen in the polycentrically organized core 2014–2019. [ABSTRACT FROM AUTHOR]

Metaphors play a crucial role in facilitating the comprehension and analysis of knowledge. "Knowledge as energy" is a well-established metaphorical framework that provides unique benefits for comprehending the dissemination of knowledge and enabling its quantification. Nevertheless, empirical studies employing this framework are limited, especially in the area of the work–energy metaphor, which primarily remains theoretical. This paper proposes an application scheme for the work– energy metaphor in interdisciplinary citation analysis. In this scheme, disciplines are considered entities; various factors that drive the progress of a discipline are considered forces; energy is considered the knowledge produced or transferred in the citations. Building upon the work–energy theorem in physics, this study developed indicators reflecting citation quality and velocity to assess interdisciplinary research progression. An empirical investigation was carried out, utilizing these indicators to evaluate the influence of interdisciplinary citations on disciplines. In the experiments, we used Library and Information Science (LIS) from 2012 to 2021 as an example to analyze the impact of interdisciplinary citations from LIS on other disciplines over two time periods. The experiments demonstrated the feasibility of the work–energy metaphorical framework proposed in this paper. It was also found that Computer Science, Management, and Business experienced the highest impact from LIS interdisciplinary citations and exhibited steady growth over a 10-year period. Environmental Science has substantial potential for the future. [ABSTRACT FROM AUTHOR]

Reference Publication Year Spectroscopy (RPYS) is a method to reveal the historical roots and landmark papers of a research field based on cited references data. RPYS visualizes how frequently cited references occur in the cited reference lists of papers published in the research field. Previous RPYS studies revealed various historical aspects of the research and publication culture in various fields of study (e.g., economy and philosophy of science). Employing RPYS, we examine a dataset of citing publications in immunology. We identify and analyze 20 cited publications occurring very frequently in the cited reference lists of these citing papers. The 20 publications shed light on the epistemic culture and the development of the field of immunology. Whereas 65% of the publications were contributions to the theoretical and empirical understanding of immunology, 35% were contributions to methodology. [ABSTRACT FROM AUTHOR]

Dissemination of knowledge through the publication of findings is a cornerstone of the academic research system. Doctoral dissertations document the findings made by early-stage researchers during their doctoral studies. However, prior research suggests that dissertations may not be effective in disseminating these findings to the broader community of researchers. We study how knowledge documented in doctoral dissertations is disseminated. Specifically, we investigate which dissertation characteristics and institutional factors are related to the number of journal publications based on these dissertations and the number of citations that these publications receive. Our analysis uses a random sample of doctoral dissertations from German universities in economics, political science, and sociology. We find that "cumulative" dissertations—dissertations consisting of a number of separate articles—are turned into three times more publications which receive three times more citations than monographic dissertations. We also find explorative evidence that dissertations written in English and empirical dissertations have higher publication-based outcomes. We conclude that a policy allowing doctoral candidates to write their dissertations in a cumulative format provides them with an opportunity to share the results of their research through publications in peer-reviewed journals. [ABSTRACT FROM AUTHOR]

This research aims to visualize the intensity of proximity between authors simultaneously cited (couplers) through a set of articles of great interest to the scientometric community. Author co-citation analysis consecutively to bibliographic coupling analysis of articles allows a more refined and significant analysis for the representation of the complex scientific structure that forms the research front of a scientific field. This refinement was entitled Co-citation Analysis between Coupler Authors (CCA). As universe of analysis, we retrieved all reference lists (cited authors) of the 10 most downloaded articles from the Scientometrics journal in 2020. Then, the coupling was established between the citing articles and following, the co-citation between all the cited authors and between the coupler authors only. There were 663 different authors cited by the 10 articles, and the analysis promoted a refinement of 89.4% authors compared to all cited authors, constituting a more reliable representation of the intellectual structure of the articles. The association between the methods will identify which and how often the citing items come together, who the coupler authors responsible for this approach are, and how the co-citation between them is configured. [ABSTRACT FROM AUTHOR]

The goal of open access is to allow more people to read and use research outputs. An observed association between highly cited research outputs and open access has been claimed as evidence of increased usage of the research, but this remains controversial. A higher citation count also does not necessarily imply wider usage such as citations by authors from more places. A knowledge gap exists in our understanding of who gets to use open access research outputs and where users are located. Here we address this gap by examining the association between an output's open access status and the diversity of research outputs that cite it. By analysing large-scale bibliographic data from 2010 to 2019, we found a robust association between open access and increased diversity of citation sources by institutions, countries, subregions, regions, and fields of research, across outputs with both high and medium–low citation counts. Open access through disciplinary or institutional repositories showed a stronger effect than open access via publisher platforms. This study adds a new perspective to our understanding of how citations can be used to explore the effects of open access. It also provides new evidence at global scale of the benefits of open access as a mechanism for widening the use of research and increasing the diversity of the communities that benefit from it. [ABSTRACT FROM AUTHOR]

The growing need for academic impact requires researchers to develop and address important ideas. In this paper, we analyze how theory has been framed and operationalized within international business scholarship, which has a long tradition of producing research that accounts jointly for multiple research contexts and levels of analysis. We focus on two key aspects of published articles: the complexity of their research questions and how the research questions are translated into testable hypotheses. We further assess how the complexity and operationalization of research questions have been received by business/management, interdisciplinary, and practice-oriented research audiences. To achieve this, we examine a sample of 423 quantitative articles published in the Journal of International Business Studies between 2005 and 2015, and consider the articles' citations during 2010–2020. Our paper provides suggestions about how authors might better frame research questions that are both important and impactful. [ABSTRACT FROM AUTHOR]

This study shows how network analyses, specifically whole network analysis, can be used to elicit network structures and identify subgroups in academic journal publishing in the field of public administration. To elicit the citation networks of the journals, we used social network analysis methods on the journal citations in the InCites Journal Citation Reports of the Web of Science (WoS) database at 4 time points: 2005, 2010, 2015, and 2020. We tested whether the citation networks had the characteristics of the small world network structure and/or a scale-free network structure. We found that the public administration citation networks became more centralized over time, while also becoming more clustered. Public Administration Review and the Journal of Public Administration Research and Theory were consistently the most central journals in the networks over the years. The citations networks were also clustered. Particularly, public policy journals, which are classified within the "public administration" category in WoS, tended to be clustered together. We conclude that the public administration journal citation networks had both scale-free characteristics and small-world characteristics in the first two decades of the twenty-first century. [ABSTRACT FROM AUTHOR]

The Matthew effect is widely used by researchers across disciplines. However, few studies have focused on this effect's magnitude variation on the background of the open access movement and expanded avenues to obtain information. Citation is the most widespread and basic form of scholarly recognition in the reward system of science, therefore, scientists are motivated to refer to the work of their peers where reference is due. This study assumes that the Matthew effect may not play a major role in science anymore and uses citations as a proxy to measure this effect, and calculates the citation fluctuation of Noble Laureates' key publications before and after winning the award during 1901–2016. The results show that the coefficient of variation of citations is smaller for publications published after 1980 than for those published before. The median of citations in chemistry is higher than that for in physics, physiology, or medicine. Additionally, over 90% of publications published after 1980 were recognized by their community pre-award, while the ratio consisted of 84% and 75% for 1940–1980 and 1900–1940, respectively. Furthermore, the time range between publication and year awarded plays a role in this phenomenon. The study suggests a potential magnitude decrease in the Matthew effect, which is a reminder that most researchers nowadays will recognize the importance of scientific breakthrough in its early stage. [ABSTRACT FROM AUTHOR]

Research metrics are known to predict many markers of scientific eminence, but fellowship in learned academies has not been examined in this context. The present research used Scopus-based citation indices, including a composite index developed by Ioannidis et al., (PLoS Biol 14:e1002501, 2016, https://doi.org/10.1371/journal.pbio.1002501) that improves cross-field comparison, to predict fellowship in the Australian Academy of Sciences (AAS). Based on ideas of a hierarchy of the sciences, the study also examined whether researchers from natural science fields were advantaged in achieving AAS fellowship relative to researchers from fields toward the social science end of the hierarchy. In a comprehensive sample of top global researchers, the composite index and its components all strongly differentiated Australian researchers who were elected as AAS fellows from those who were not. As predicted, when composite index scores were statistically controlled, researchers in physical and mathematical sciences were more likely to achieve fellow status than biological scientists, who were much more likely to achieve it than psychological, cognitive, and social scientists. Researchers in basic science fields also had an election advantage over those in more applied and technological fields. These findings suggest that recognition by learned academies may be predicted by citation indices, but may also be influenced by the perceived hardness, prestige, and purity of research fields. [ABSTRACT FROM AUTHOR]

A high level of citations is generally associated with the exceptional influence of an article. Authors of several highly cited articles are thus considered and scrutinized as influential members within their scientific discipline and beyond when their activity spans several disciplines. Identifying individuals who have made outstanding contributions to science is the motivation behind the Highly Cited Researchers (HCR) list published annually by a commercial company. This article is devoted to the case of highly cited researchers affiliated with French institutions. We study the characteristics of the HCR population: productivity, gender bias, career and persistence on the list, collaboration network, and scientific integrity. Then, from the annual lists of HCRs from 2014 to 2022, we examine what the number of HCRs tells us about France's place in the world scientific arena, its evolution over a decade, and its geographical and institutional distribution. We discuss whether the population of French HCRs constitutes a scientific elite by examining the case of Mathematics. Finally, we discuss several indicators which could be used to verify that a researcher is close to the threshold to enter the list. [ABSTRACT FROM AUTHOR]

With the rapid growth of social media, knowledge diffusion of scientific literature comprises not only citation trajectory but also dimension of societal impact. For special types of knowledge diffusion, especially Sleeping Beauties in Science (SBs), it is essential but not adequate to only use citation analysis to measure its trajectory. The impact and value of scientific literature can be fully revealed only by integrating the diffusion trajectory of citation and social media. This study focuses on identifying the possible problems in research on SBs and emphasizes the necessity of Altmetrics-based SB (A-SB) to solve them. Referring to the practice in our earlier study, we identified 7 A-SBs and 11 citation-based SBs (C-SB). The comparative analysis of interdisciplinary and impact between A-SB and C-SB revealed the likely defects in the traditional C-SB research on the measurement of impact in knowledge diffusion, the mining of potential mechanism, the explanation of scientific knowledge diffusion pathways and the discovery of some key scientific literature, and that A-SB plays a vital role in these aspects. In contrast to C-SB, A-SB also offers the possibility to explore pathways for the diffusion of scientific knowledge. Furthermore, a typical A-SB case analysis suggested that A-SB has a unique advantage in discovering some innovative research with potential value ahead. [ABSTRACT FROM AUTHOR]

A key feature of questionable journals is a lack of adequate peer review of their articles. Content of thus unknown quality may be utilised by unsuspecting practitioners or incorporated into peer-reviewed research, becoming legitimised. It is therefore necessary to examine the citation patterns of articles in questionable journals to understand their impact and reach. Similar research has tended to focus on authors from low- and middle-income countries. As such, this study investigates the profile and impact of research in questionable journals by authors in Germany. Questionable journals were identified by matching journals with articles by authors at German institutions from Dimensions to Cabell's Predatory Reports. Metadata for these articles and a comparative sample of articles in non-questionable journals were extracted from Dimensions and the 3 year citations, self-citations, uncited rate, profile of co-authoring and citing countries, and institution type of authors were compared between groups. Nearly 600 articles in 88 questionable journals were published by German authors in 2010–2020. Three-quarters were in the medical and health sciences. Medical articles in questionable journals received significantly fewer citations than similar articles in non-questionable journals. However, articles in questionable journals were still extensively cited in 1736 primarily non-questionable journals. Self-citations accounted for only 12% of these citations. Authors from non-university medical facilities were over-represented in articles in questionable journals. System-level changes are necessary to eliminate questionable journals and shift high-quality research into reputable venues. [ABSTRACT FROM AUTHOR]

This study examines the visibility, impact, and applications of bibliometric software tools in the peer-reviewed literature through a "Cited Reference Search" using the Web of Science (WOS) database. A total of 2882 citing research articles to eight bibliometric software tools were extracted from the WOS Core Collection between 2010 and 2021. These citing articles are analyzed by publication year, country, publication title, publisher, open access level, funding agency, and WOS category. Mentions of bibliometric software tools in Author Keywords and KeyWords Plus are also compared. The VOSviewer software is utilized to identify specific research areas by discipline from the keyword co-occurrences of the citing articles. The findings reveal that while bibliometric software tools are making a noteworthy impact and contribution to research, their visibility through referencing, Author Keywords, and KeyWords Plus is limited. This study serves as a clarion call to raise awareness and initiate discussions on the citing practices of software tools in scholarly publications. [ABSTRACT FROM AUTHOR]

Research on the COVID-19 pandemic has produced an incredible volume of social science research. To explore the initial areas of COVID-19 scholarship, the following study uses bibliometric co-citation network analysis on data from Clarivate's Web of Science database to analyze 3327 peer-reviewed studies published during the first year of the pandemic and their 107,396 shared references. Findings indicate nine distinct disciplinary research clusters centered around a single medical core of COVID-19 pandemic research. Topics ranging from tourism collapse, fear scales, financial contagion, health surveillance, shifts in crime rates, quarantine psychology, and collective trauma among others are found to have emerged in this initial phase of research as covid spread across the world. A corresponding infodemic highlights early communication challenges and a broader need to thwart misinformation. As this body of work continues to grow across the social sciences, key intersections, shared themes, and long-term implications of this historic event are brought into view. [ABSTRACT FROM AUTHOR]

The Cochrane Database of Systematic Reviews is internationally recognized as one of the best sources of evidence within medical research. Nevertheless, a considerable amount of Cochrane reviews in the Cochrane Database of Systematic Reviews (CDSR) have not been updated for more than 5.5 years and are therefore considered inactive. This study's aim was to evaluate if these are still used in academia. The study included 7,729 Cochrane reviews from the CDSR. Their Digital Object Identifiers (DOIs) were linked with citation data from the search engine The Lens. The citation pattern of 3,735 inactive reviews in the CDSR were analyzed and the results were adjusted for inflation in citation. A subgroup analysis of citing motives was performed for the most recent citations of the 20 most outdated reviews. In 2020, 41% of all citations of Cochrane reviews, were of reviews that had not been updated for more than 5.5. years. 5 years after last update, Cochrane reviews were on average cited 8.6 times per year. Twenty-five percent of Cochrane reviews were still cited 10 years after last update and were on average cited 4.3 times in the 10th year. None of the most recent citations of the 20 most outdated reviews indicated directly that the review was out of date. Cochrane reviews continued to be cited even though they were not being updated. This could pose a problem if they do not represent the most up-to-date evidence, as it may lead to the distribution of outdated evidence or misinformation. [ABSTRACT FROM AUTHOR]

The Microeconomic Theory by (Mas-Colell et al., Microeconomic Theory, Oxford University Press, 1995) has become the standard microeconomics textbook in economics PhD programs shortly after its publication. Despite 25 years having passed since the first and only edition, the textbook is still used predominantly in these programs. In this paper, we investigate the citation performance of the references in the textbook after 1995. We selected a comparison group of publications that have similar citation performance as the references in the textbook before 1995. We find that the references in the textbook have performed better than the comparison group of publications after 1995. Therefore, we conclude that one of the reasons for the success of the textbook might the careful choice of its references. [ABSTRACT FROM AUTHOR]

National scientific qualification (NSQ) is a procedure to regulate access to Italian academic positions. An increased use of self-citations could favor the achievement of the minimum bibliometric requirements. The aim of this study was to retrospectively analyze the self-citing behavior of successful candidates who applied for the NSQ in the Allied Health Professions (AHP) scientific field. Bibliometric indexes of all candidates qualified in the three first sessions (2012, 2013, and 2016) were retrieved from the Scopus database. We developed a new index (ΔSCR) to detect changes in the candidate's habits based on the difference between the Self Citation Rate (SCR) in the year preceding NSQ and that of the previous 10 years. The Kruskal–Wallis test was used to analyze the ΔSCR between sessions. Multivariate regressions were run to investigate the relationship between ΔSCR and six independent factors. Differences in ΔSCR were found between 2012 and 2013 (p = 0.008), between 2013 and 2016 (p < 0.0001), but not between 2012 and 2016 (p = 1.000). Regressions showed highest R2 in ΔSCR ≥ 10 subsets (2012: R2 = 0.373; 2013: R2 = 0.645; 2016: R2 = 0.511). The difference in citation habits (ΔC) was a significant ΔSCR predictor in 2012 and 2013, while publication habits (ΔP) and the difference in the H-index with vs. without self-citations (ΔH) were significant variables in 2012 and 2016, respectively. In the AHP sector, there was an increase in the use of self-citations in the 2013 session. Higher ΔSCR was associated with ΔC, ΔH and ΔP. [ABSTRACT FROM AUTHOR]

Scientific collaboration is getting tremendous attention from scholars and becoming the most common way of producing research works from different disciplines, enabling them to solve complex problems. Nevertheless, when the number of collaborators increases in research work, it becomes challenging to single out and recognize one scholar who contributes the most to the collaboration team of multiauthored publications. Hence, determining an influential author either from multiauthored papers or co-authorship networks is an interesting research problem. To address these problems, we develop a citation and similarity-based author ranking method, namely CLARA, that captures the influential author in multiauthored publications. The method considers attributes of publications such as citing papers and co-cited papers and similarity between publications. Firstly, the method computes the contribution of the co-authors in a given paper by employing fractional counting metrics. Secondly, it computes the contextual similarity between the given paper and its co-cited papers. Finally, the method ranks each co-author using the mathematically defined metric, called KeyScore, and discovers the "key" author among the co-authors of the given paper. We validate our method by extracting the papers of the "Chinese Outstanding Youth" winning researchers from the Microsoft Academic Graph dataset. The experimental results show that the CLARA method performs well in identifying key authors accurately and effectively, despite the position of the authors in the author list of their corresponding papers. [ABSTRACT FROM AUTHOR]

Clarivate Analytics announces highly cited researchers (HCRs) every November to recognise true pioneers in their respective fields over the last decade who are one in 1000 according to citation analysis based on the Web of Science™ database. However, the scientometric rules underlying HCR selections have constantly evolved over the years; thus, a comparative study between HCRs' academic relevance before and after 2018, when the cross field started to be included in HCR statistics, is essential. This paper evaluated the consistency of measurements in 2017 and 2018 by analysing HCR distributions by different regions and Essential Science Indicators (ESI) fields, studied the effects of introducing the cross-field category to the original 21 ESI fields, and portrayed the accurate picture of HCR distributions by region and subject without the influence of measurement biases. The cross field is believed to exert great impact on regional and field-specific HCR distributions, especially for research fields with HCR counts larger than 150. It was other countries and regions except the US and China that grew with the greatest momentum after the inclusion of cross-field HCRs. [ABSTRACT FROM AUTHOR]

In a recent contribution in this journal, Gagolewski et al. (Scientometrics 127(5):2829–2845, 2022) study a new model—the so-called 3 dimensions of scientific impact (3DSI) model—for representing a rank size distribution. The model depends on three parameters/dimensions: the total number of papers, the total number of citations and a third parameter, ρ , recognized by the authors as a shape parameter. We prove that ρ is an equivalent Gini coefficient. [ABSTRACT FROM AUTHOR]

Grey literature encompasses documents not published in academic journals or books. Some grey literature has substantial societal importance, such as medical guidelines, government analyses and pressure group reports. Academic research cited in such documents may therefore have had indirect societal impact, such as in policy making, clinical practice or legislation. Identifying citations to academic research from grey literature may therefore help assess its societal impacts. This is difficult, however, due to the variety of document and referencing formats used in grey literature, even from a single organisation. In response, this study introduces and tests a semi-automatic method to match academic journal articles with unstandardised grey literature cited references. For this, the metadata (lead author last name, title, year) of 2.45 million UK Russell Group university outputs was matched against a 100-document sample of UK government grey literature to assess the accuracy of 21 matching heuristics. The optimal method (lead author last name and title in either order, maximum of 200 characters apart) is sufficiently accurate and scalable to make the task of matching research outputs to grey literature references feasible. The method was then applied to 3347 government publications, showing approximately 23% of UK government grey literature in this study contained at least one reference to UK Russell Group university output, and of this grey literature, an average of 3.79 references were present per document. The applied method also shows that economics and environmental science academic research is most cited between 2010 and 2018. [ABSTRACT FROM AUTHOR]

Author bibliographic coupling analysis (ABCA) is an extension of bibliographic coupling theory at the author level and is widely used in mapping intellectual structures and scholarly communities. However, the assumption of equal citations and the complete dependence on explicit counts may affect its effectiveness in today's complex context of discipline development. This research proposes a new approach that uses multiple full-text data to improve ABCA called enhanced author bibliographic coupling analysis. By mining the semantic and syntactic information of citations, the new approach considers more diverse dimensions as the basis of author bibliographic coupling strength. Comparative empirical research was then conducted in the field of oncology. The results show that the new approach can more accurately reveal the relevant relations between authors and map a more detailed domain intellectual structure. [ABSTRACT FROM AUTHOR]

Being cited by policy documents is an important indicator for assessing the policy impact of research. The purpose of this paper was to examine the associations between an article's scientific collaborations and its citations received from policy documents. Research articles published between 2000 and 2018 in 86 journals under the category of "Information Science & Library Science" (LIS) in Journal Citation Reports 2020 were selected as the data sample (n = 40,137). The metadata of the articles was extracted from the Web of Science. The outcome variable of this study, policy citations of each article, were obtained from Overton (one of the largest policy citation databases). Standard negative binomial regression models and zero-inflated negative binomial regression models were conducted to examine the dataset. Linear regression models and six selected LIS journals were used to check the robustness of the results. The results revealed that the number of countries had significant and positive associations with policy citations (p < 0.001), the number of authors and the number of affiliations had no significant associations with policy citations, while controlling the other variables. [ABSTRACT FROM AUTHOR]

This study proposes a method for assessing the impact of scientific communication on their citation paths beyond conventional direct citations. The proposed method considers the contribution of scientific communication to their nth generation citations as a basis for calculating residual citations. Residual citations that are lost due to citation practices termed "Obliteration by Incorporation" and the "Palimpsestic Syndrome" in consequent citations in the second, third or nth generations are reconstituted. The proposed method is based on the semantic similarity between the citation contexts of a publication and those of its nth generation citations in their n + 1th generation citations. The proposed method was demonstrated using a sample of biomedical publications with ten base articles and their five generations of citations. Like the cascading citation system, residual citations accruing to articles from their generations of citations decreased as the number of generations increased. However, residual citation weights accrued to publications at all generation levels were statistically different between the proposed residual citation and the cascading citation system. This method introduces a new frontier that assesses the depth of impact of a publication (beyond the conventional direct citation level). [ABSTRACT FROM AUTHOR]

The soaring number of researchers has led to increasingly intense competition in academia. Early identification of scientists' potential is a practical but difficult issue currently attracting escalating attention. This study takes the business field as an example and explores whether early publishing in top journals is an effective yardstick to recognise scientists who will have better academic performance in their careers. We extract the career records of publication and citations for 1933 business scientists with stable and continuous publication records from the combination of the ORCID and Scopus databases. Through regression analysis and various checks, we find that researchers publishing in top journals early in their careers indeed perform better subsequently compared to peers with similar early career profiles but no top journal publications. Our research sheds light on a new perspective for early identification of potential star scientists, especially in the business field, and justifies encouraging junior researchers to devote themselves to publishing in top-ranked peer-reviewed journals. [ABSTRACT FROM AUTHOR]

Interdisciplinary interaction and integration have become major features of current science and technology development. Hence, ways to measure the strength of the interdisciplinary interactions between two given disciplines has become a crucial issue. In this study, we propose a novel framework for measuring interdisciplinary interaction that is based on both citation analysis and semantic analysis. Within the framework, direct citations combined with bibliographic coupling reflect citation relationship of interdisciplinary knowledge, while an LDA model combined with a word embedding model are used to explore the integration and diffusion of knowledge via semantic similarity. The strength of the interdisciplinary interactions is then assessed with an entropy weighting method. A case study on the interactions between Information & Library Science and six other disciplines demonstrates the efficacy and reliability of the framework. [ABSTRACT FROM AUTHOR]

Although citations are used as a quantifiable, objective metric of academic influence, references could be added to a paper solely to inflate the perceived influence of a body of research. This reference list manipulation (RLM) could take place during the peer-review process, or prior to it. Surveys have estimated how many people may have been affected by coercive RLM at one time or another, but it is not known how many authors engage in RLM, nor to what degree. By examining a subset of active, highly published authors (n = 20,803) in PubMed, we find the frequency of non-self-citations (NSC) to one author coming from a single paper approximates Zipf's law. Author-centric deviations from it are approximately normally distributed, permitting deviations to be quantified statistically. Framed as an anomaly detection problem, statistical confidence increases when an author is an outlier by multiple metrics. Anomalies are not proof of RLM, but authors engaged in RLM will almost unavoidably create anomalies. We find the NSC Gini Index correlates highly with anomalous patterns across multiple "red flags", each suggestive of RLM. Between 81 (0.4%, FDR < 0.05) and 231 (1.1%, FDR < 0.10) authors are outliers on the curve, suggestive of chronic, repeated RLM. Approximately 16% of all authors may have engaged in RLM to some degree. Authors who use 18% or more of their references for self-citation are significantly more likely to have NSC Gini distortions, suggesting a potential willingness to coerce others to cite them. [ABSTRACT FROM AUTHOR]

For efficient research and development (R&D) management, estimating the economic value of patents is becoming increasingly necessary. When estimating the economic value of patents, technology lifetime is one of the most important factors to be considered. The Pareto/non-negative binomial distribution (NBD) model is a stochastic model that can estimate the technology lifetime based on patent citation data. However, the Pareto/NBD model has some limitations. First, the model assumes that the technology of a patent is active until it is cited by another patent even though the cited patent is expired. Second, the probability distribution of the technology lifetime for a patent group always has a mode of zero, which implies that patent technologies are immediately replaced by other technologies. To address these issues, we propose a more generalized method that estimates the technology lifetime of a patent based on a modified gamma Gompertz with NBD (G/G/NBD) model. We apply the proposed methodology to estimate the lifetime of US patents in three communication-related technology areas. The case study and sensitivity analysis showed reliable estimates by the proposed methodology, where technology lifetimes were estimated within the patents' term based on the proposed model while the existing model often resulted in their estimated lifetime being greater than the patent term. [ABSTRACT FROM AUTHOR]

Scientific research builds on previous studies and scientifically proven knowledge. Researchers must master the recent developments in the field when designing research to answer new questions. Today, the accessibility of research literature is abundant due to digitized publications, extensive coverage of citation indexes, and several literature databases. The means for conducting systematic literature reviews have greatly improved. In recent years, a lot of research with methods, such as systematic literature reviews, literature mapping, and visualizing studies, has been published. Despite the tools having been perfected, they still have limitations. Particularly, database selection for a literature search sets a bias, because the citation indexes differ in coverage according to the scientific domain. In this paper, bibliometric data from two citation indexes (Web of Science and Scopus) are combined for the purposes of bibliometric analyses in the context of inter-firm relationships. The combination process requires a lot of unifying and repairing of data in practice that is referred as data wrangling. This study describes the process steps and the lessons learned and considers the amount of effort required. [ABSTRACT FROM AUTHOR]

Research on the impact of and attention given to journal covers is a crucial research topic in academia. This study investigated whether a paper featured on the cover of a journal receives more citations and higher usage than non-cover papers. Unlike previous studies that focused on just a few prestigious journals, we analyzed the citations and usage counts of 3196 cover and 36,652 non-cover papers published in 42 cell biology journals from 2011 to 2015. To address the above question, four new indicators were used to compare descriptive differences in stratified sets, and both linear regression model analysis and robustness testing were applied to further explore the relationships. Our main results showed that being a cover paper has positive and significant relationships both with citations and usage counts. Moreover, additional analyses show that the two relationships are strengthened in top-tier journals, and the main effects remain robust when we consider the influence of author ability. This new exploration of factors relevant for citations and usage counts in this empirical analysis consolidates and broadens the findings of previous studies. [ABSTRACT FROM AUTHOR]

Citation network analysis is one of the most developed techniques in science mapping. Various types of citation analysis have been proposed in the literature such as direct citation, co-citation and bibliographic coupling. Networks based on these citation analysis types have been used to reveal discipline structure, central players and emerging trends in STEM and social sciences. However, in the humanities large-scale citation network analysis is still underexplored, mainly due to the lack of comprehensive data sources and varying publication practices. In this paper, we investigate the unique characteristics and needs of citation analysis in the historical humanities and propose a generic framework for systematic generation and analysis of different types of citation networks based on several variables and the essential distinction between citations of primary and secondary sources. The proposed methodology was applied to a corpus of over 15,000 (both primary and secondary) books related to the research field of ancient Mediterranean religions. The obtained results show that in order to gain a deep and comprehensive understanding of a discipline's structure it is beneficial to compare and combine the findings of several types of networks rather than focus on a single network analysis. Comparative community analysis of the networks reveals the existence of a disciplinary core only in the primary literature corpus and a hierarchical sub-discipline structure of the examined research field. [ABSTRACT FROM AUTHOR]

Research on academic paper ranking has received great attention in recent years, and many algorithms have been proposed to automatically assess a large number of papers for this purpose. How to evaluate or analyse the performance of these ranking algorithms becomes an open research question. Theoretically, evaluation of an algorithm requires to compare its ranking result against a ground truth paper list. However, such ground truth does not exist in the field of scholarly ranking due to the fact that there does not and will not exist an absolutely unbiased, objective, and unified standard to formulate the impact of papers. Therefore, in practice researchers evaluate or analyse their proposed ranking algorithms by different methods, such as using domain expert decisions (test data) and comparing against predefined ranking benchmarks. The question is whether using different methods leads to different analysis results, and if so, how should we analyse the performance of the ranking algorithms? To answer these questions, this study compares among test data and different citation-based benchmarks by examining their relationships and assessing the effect of the method choices on their analysis results. The results of our experiments show that there does exist difference in analysis results when employing test data and different benchmarks, and relying exclusively on one benchmark or test data may bring inadequate analysis results. In addition, a guideline on how to conduct a comprehensive analysis using multiple benchmarks from different perspectives is summarised, which can help provide a systematic understanding and profile of the analysed algorithms. [ABSTRACT FROM AUTHOR]

Judging value of scholarly outputs quantitatively remains a difficult but unavoidable challenge. Most of the proposed solutions suffer from three fundamental shortcomings: they involve (i) the concept of journal, in one way or another, (ii) calculating arithmetic averages from extremely skewed distributions, and (iii) binning data by calendar year. Here, we introduce a new metric Co-citation Percentile Rank (CPR), that relates the current citation rate of the target output taken at resolution of days since first citable, to the distribution of current citation rates of outputs in its co-citation set, as its percentile rank in that set. We explore some of its properties with an example dataset of all scholarly outputs from University of Jyväskylä spanning multiple years and disciplines. We also demonstrate how CPR can be efficiently implemented with Dimensions database API, and provide a publicly available web resource JYUcite, allowing anyone to retrieve CPR value for any output that has a DOI and is indexed in the Dimensions database. Finally, we discuss how CPR remedies failures of the Relative Citation Ratio (RCR), and remaining issues in situations where CPR too could potentially lead to biased judgement of value. [ABSTRACT FROM AUTHOR]

The top-1% most-highly-cited articles are watched closely as the vanguards of the sciences. Using Web of Science data, one can find that China had overtaken the USA in the relative participation in the top-1% (PP-top1%) in 2019, after outcompeting the EU on this indicator in 2015. However, this finding contrasts with repeated reports of Western agencies that the quality of China's output in science is lagging other advanced nations, even as it has caught up in numbers of articles. The difference between the results presented here and the previous results depends mainly upon field normalizations, which classify source journals by discipline. Average citation rates of these subsets are commonly used as a baseline so that one can compare among disciplines. However, the expected value of the top-1% of a sample of N papers is N / 100, ceteris paribus. Using the average citation rates as expected values, errors are introduced by (1) using the mean of highly skewed distributions and (2) a specious precision in the delineations of the subsets. Classifications can be used for the decomposition, but not for the normalization. When the data is thus decomposed, the USA ranks ahead of China in biomedical fields such as virology. Although the number of papers is smaller, China outperforms the US in the field of Business and Finance (in the Social Sciences Citation Index; p <.05). Using percentile ranks, subsets other than indexing-based classifications can be tested for the statistical significance of differences among them. [ABSTRACT FROM AUTHOR]

Scholarly books are important outputs in some fields and their many publishing formats seem to introduce opportunities to scrutinize their impact. As there is a growing interest in the publisher-enforced massive collection of ebooks in libraries in the past decade, this study examined how this influences the relationship that library print holdings (LPH), library electronic holdings (LEH) and total library holdings (TLH) have with other metrics. As a follow up study to a previous research on OCLC library holdings, the relationship between library holdings and twelve other metrics including Scopus Citations, Google Books (GB) Citations, Goodreads engagements, and Altmetric indicators were examined for 119,794 Scopus-indexed book titles across 26 fields. Present study confirms the weak correlation levels observed between TLH and other indicators in previous studies and contributes additional evidence that print holdings can moderately reflect research, educational and online impact of books consistently more efficient than eholdings and total holdings across fields and over time, except for Mendeley for which eholdings slightly prevailed. Regression models indicated that along with other dimensions, Google Books Citations frequently best explained LPH (in 14 out of 26 fields), whereas Goodreads User counts were weak, but the best predictor of both LEH and TLH (in 15 fields out of 26), suggesting significant association of eholdings with online uptake of books. Overall, findings suggest that inclusion of eholdings overrides the more impactful counts of print holdings in Total Library Holdings metric and therefore undermines the statistical results, whilst print holdings has both statistically and theoretically promising underlying assumptions for prediction of impact of books and shows greater promise than the general Library Holding metric for book impact assessment. Thus, there is a need for a distinction between print and electronic holding counts to be made, otherwise total library holding data need to be interpreted with caution. [ABSTRACT FROM AUTHOR]

Citation is an important process of scientific activities, reflecting the inheritance and development of knowledge. However, citations representing different sentiment polarities function differently in knowledge construction, especially negative citations holding critical views, which deserve more in-depth study. This paper selected papers on SVM from 1995 to 2020, and used the stratified random sampling method to obtain 3,337 citation sentences from 46,157 citations, coding several attributes such as citation polarity, to analyze the relationship between negative citation and the impact of cited paper and the role of negative citation in the development of SVM technology. The results of the study found that negative citations do not reduce the literature impact; papers with a certain negative citation ratio would have a higher impact; and the impact of those partially dismissed papers would be even higher. In addition, negative citation presents different characteristics in different periods of the development of SVM, which has a certain promotion effect on the improvement of this technology. [ABSTRACT FROM AUTHOR]

There are many attempts have been made to measure the research outcome and impact of any author or institutes using h-index, g-index, e-index, s-index, m-index and other parameters recently. It becomes more complex when the performance is measured from 2 million documents and more than 30 million citations. In this case, domain based expert and performance analysis for the given time phase is indeed requirement for a fair comparison among two institutes (or authors) rather than whole data sets. One of the reason is many institutes (or authors) publishes several papers randomly in distinct domain for document or citation count rather than a projected domain. To solve this issue, a new metric called as ''t-index" is introduced in this paper using Shannon entropy and yearly average of h-index. The proposed method is illustrated for computer science domain using the Scopus data. The obtained results from t-index are compared with h-index for validating the results. [ABSTRACT FROM AUTHOR]

This study investigates the potential of citation analysis of Ph.D. theses to obtain valid and useful early career performance indicators at the level of university departments. For German theses from 1996 to 2018 the suitability of citation data from Scopus and Google Books is studied and found to be sufficient to obtain quantitative estimates of early career researchers' performance at departmental level in terms of scientific recognition and use of their dissertations as reflected in citations. Scopus and Google Books citations complement each other and have little overlap. Individual theses' citation counts are much higher for those awarded a dissertation award than others. Departmental level estimates of citation impact agree reasonably well with panel committee peer review ratings of early career researcher support. [ABSTRACT FROM AUTHOR]

Citation analysis has been applied to map the landscape of scientific disciplines and to assess the impact of publications. However, it is limited in that it assumes all citations to be of equal weight. Doing away with this assumption could make such studies even more insightful. Current developments in this regard focus on the evaluation of the syntactic and semantic qualities of the text that surrounds citations. Still lacking, however, are computational techniques to unpack the thematic context in which citations appear. It is against this backdrop that we propose a text clustering approach to derive contextual aspects of individual citations and the relationship between cited and citing work in an automated and scalable fashion. The method reveals a focal publication's absorption and use within the scientific community. It can also facilitate impact assessments at all levels. In addition to analyzing individual publications, the method can also be extended to creating impact profiles for authors, institutions, disciplines, and regions. We illustrate our results based on a large corpus of full-text articles from the field of Information systems (IS) with the help of exemplary visualizations. In addition, we provide a case study, the scientific impact of the Technology acceptance model. This way, we not only show the usefulness of our method in comparison to existing techniques but also enhance the understanding of the field by providing an in-depth analysis of the absorption of a key IS theoretical base. [ABSTRACT FROM AUTHOR]

In recent years, increased stakeholder pressure to transition research to Open Access has led to many journals converting, or 'flipping', from a closed access (CA) to an open access (OA) publishing model. Changing the publishing model can influence the decision of authors to submit their papers to a journal, and increased article accessibility may influence citation behaviour. In this paper we aimed to understand how flipping a journal to an OA model influences the journal's future publication volumes and citation impact. We analysed two independent sets of journals that had flipped to an OA model, one from the Directory of Open Access Journals (DOAJ) and one from the Open Access Directory (OAD), and compared their development with two respective control groups of similar journals. For bibliometric analyses, journals were matched to the Scopus database. We assessed changes in the number of articles published over time, as well as two citation metrics at the journal and article level: the normalised impact factor (IF) and the average relative citations (ARC), respectively. Our results show that overall, journals that flipped to an OA model increased their publication output compared to journals that remained closed. Mean normalised IF and ARC also generally increased following the flip to an OA model, at a greater rate than was observed in the control groups. However, the changes appear to vary largely by scientific discipline. Overall, these results indicate that flipping to an OA publishing model can bring positive changes to a journal. [ABSTRACT FROM AUTHOR]

Some complementary and alternative medicines (CAM) are frequently criticised for being based on faith rather than scientific evidence. Despite this, researchers, academic departments, and institutes teach and investigate them. This article assesses whether the scholarship produced by four CAMs is valued by the academic community in terms of citations, and whether the level of citations received might be detrimental to academic authors' careers. Based on an analysis of acupuncture, chiropractic, homeopathy, and osteopathy journal articles indexed in Scopus 1996–2020, the results show that the prevalence of the four areas vary substantially internationally, with acupuncture eclipsing the others in East Asia but homeopathy being more common in India and Brazil. The main broad fields publishing these specialties are Medicine, Nursing, Health Professions, Veterinary Science, and Neuroscience. Whilst the research tends to be cited at a below average rate in most broad fields (n = 27) and years (1996–2017), acupuncture, chiropractic, and homeopathy are exceptions in some broad fields, including some core areas. Thus, studying these alternative medicines may not always lead to research that tends to be ignored in academia, even if many scientists disparage it. As a corollary, citation analysis cannot be relied on to give low scores to widely disparaged areas of scholarship. [ABSTRACT FROM AUTHOR]

Research and development are central to economic growth, and a key challenge for countries of the global South is that their research performance lags behind that of the global North. Yet, among Southern researchers, a few significantly outperform their peers and can be styled research "positive deviants" (PDs). In this paper we ask: who are those PDs, what are their characteristics and how are they able to overcome some of the challenges facing researchers in the global South? We examined a sample of 203 information systems researchers in Egypt who were classified into PDs and non-PDs (NPDs) through an analysis of their publication and citation data. Based on six citation metrics, we were able to identify and group 26 PDs. We then analysed their attributes, attitudes, practices, and publications using a mixed-methods approach involving interviews, a survey and analysis of publication-related datasets. Two predictive models were developed using partial least squares regression; the first predicted if a researcher is a PD or not using individual-level predictors and the second predicted if a paper is a paper of a PD or not using publication-level predictors. PDs represented 13% of the researchers but produced about half of all publications, and had almost double the citations of the overall NPD group. At the individual level, there were significant differences between both groups with regard to research collaborations, capacity development, and research directions. At the publication level, there were differences relating to the topics pursued, publication outlets targeted, and paper features such as length of abstract and number of authors. [ABSTRACT FROM AUTHOR]

One of the most fundamental issues in academia today is understanding the differences between legitimate and questionable publishing. While decision-makers and managers consider journals indexed in popular citation indexes such as Web of Science or Scopus as legitimate, they use two lists of questionable journals (Beall's and Cabell's), one of which has not been updated for a few years, to identify the so-called predatory journals. The main aim of our study is to reveal the contribution of the journals accepted as legitimate by the authorities to the visibility of questionable journals. For this purpose, 65 questionable journals from social sciences and 2338 Web-of-Science-indexed journals that cited these questionable journals were examined in-depth in terms of index coverages, subject categories, impact factors and self-citation patterns. We have analysed 3234 unique cited papers from questionable journals and 5964 unique citing papers (6750 citations of cited papers) from Web of Science journals. We found that 13% of the questionable papers were cited by WoS journals and 37% of the citations were from impact-factor journals. The findings show that neither the impact factor of citing journals nor the size of cited journals is a good predictor of the number of citations to the questionable journals. [ABSTRACT FROM AUTHOR]

In this article, we show the results of a quantitative and qualitative analysis of open citations on a popular and highly cited retracted paper: "Ileal-lymphoid-nodular hyperplasia, non-specific colitis and pervasive developmental disorder in children" by Wakefield et al., published in 1998. The main purpose of our study is to understand the behavior of the publications citing one retracted article and the characteristics of the citations the retracted article accumulated over time. Our analysis is based on a methodology which illustrates how we gathered the data, extracted the topics of the citing articles and visualized the results. The data and services used are all open and free to foster the reproducibility of the analysis. The outcomes concerned the analysis of the entities citing Wakefield et al.'s article and their related in-text citations. We observed a constant increasing number of citations in the last 20 years, accompanied with a constant increment in the percentage of those acknowledging its retraction. Citing articles have started either discussing or dealing with the retraction of Wakefield et al.'s article even before its full retraction happened in 2010. Articles in the social sciences domain citing the Wakefield et al.'s one were among those that have mostly discussed its retraction. In addition, when observing the in-text citations, we noticed that a large number of the citations received by Wakefield et al.'s article has focused on general discussions without recalling strictly medical details, especially after the full retraction. Medical studies did not hesitate in acknowledging the retraction of the Wakefield et al.'s article and often provided strong negative statements on it. [ABSTRACT FROM AUTHOR]

Scientific articles often include in-text citations quoting from external sources. When the cited source is an article, the citation context can be analyzed by exploring the article full-text. To quickly access the key information, researchers are often interested in identifying the sections of the cited article that are most pertinent to the text surrounding the citation in the citing article. This paper first performs a data-driven analysis of the correlation between the textual content of the sections of the cited article and the text snippet where the citation is placed. The results of the correlation analysis show that the title and abstract of the cited article are likely to include content highly similar to the citing snippet. However, the subsequent sections of the paper often include cited text snippets as well. Hence, there is a need to understand the extent to which an exploration of the full-text of the cited article would be beneficial to gain insights into the citing snippet, considering also the fact that the full-text access could be restricted. To this end, we then propose a classification approach to automatically predicting whether the cited snippets in the full-text of the paper contain a significant amount of new content beyond abstract and title. The proposed approach could support researchers in leveraging full-text article exploration for citation analysis. The experiments conducted on real scientific articles show promising results: the classifier has a 90% chance to correctly distinguish between the full-text exploration and only title and abstract cases. [ABSTRACT FROM AUTHOR]

The purpose of this article is to evaluate the coverage of accounting topics in 2018 and 2019 by the high-ranked and cited journals of popular international publishers. To achieve this, the study provides (1) research on the proportion of accounting journals in the international publishers; (2) identification of the largest publishers by the number of accounting journals; (3) a check of the high-ranked and cited accounting journals according to the journals' websites, the SCImago database, and Web of Science database; (4) investigation of the trend in the number of accounting publications in 2018–2019 compared with 2016–2017 by SSRN, IDEAS/RePEc, and DOAJ; (5) a detailed overview of 1749 accounting publications for 2018 and 2019 using the reference databases of such international publishers as Blackwell, Elsevier, American Accounting Association, Kluwer Academic Publishers, Oxford University Press, Cambridge University Press, and Springer; (6) a self-developed classification of the accounting topics into 14 main directions; and (7) an assessment of the extent of coverage of accounting topics by each journal. The research methods are based on a cross-sectional survey between the website of each publisher and the SCImago database, and on a bibliometric analysis of the metrics and citation impact, the number and proportion of articles in the "major" journals in accounting, and the major bibliometrics databases. SCImago, as the main bibliometrics database, was used for the first time to identify the top-ranked and cited journals. This study highlights the importance of accounting in international publications in the high-ranked and cited journals, emphasizing the actual publications obtained in 2018–2019. The results indicate that a high quartile or high international citation level does not determine the full coverage of accounting topics in a journal. It was found that assets, control, management accounting, and financial reporting were the most frequently published topics in 2018 and 2019. The blockchain technology and IFRS research in accounting were published within 2018–2019 in only 125 articles (7.14%) by 26 accounting journals among the high-ranked and cited journals with an obtained high coverage of accounting topics. This study may help scientists to select a journal for publishing or researching an appropriate accounting topic. Moreover, to increase the coverage extent of accounting topics, the analysis and classification of publication topics conducted in this work are also recommended to editorial boards of accounting journals as information regarding the least disclosed accounting topics over the last 2 years. [ABSTRACT FROM AUTHOR]