Journal of Informetrics最新文献

{"title":"Hyperprolific authorship: Unveiling the extent of extreme publishing in the ‘publish or perish’ era","authors":"Giovanni Abramo ,&nbsp;Ciriaco Andrea D'Angelo","doi":"10.1016/j.joi.2025.101658","DOIUrl":"10.1016/j.joi.2025.101658","url":null,"abstract":"<div><div>The increasing pressure of the “publish or perish” academic culture has contributed to the rise of hyperprolific authors—researchers who produce an exceptionally high number of publications. This study investigates the global phenomenon of hyperprolific authorship by analyzing the bibliometric data of over two million scholars across various disciplines from 2017 to 2019. Using field-specific thresholds to identify hyperprolific authors, we explore their geographic and disciplinary distributions, the impact of their publications, and their collaboration patterns. The results reveal that hyperprolific authors are concentrated in fields such as Clinical Medicine, Biomedical Research, and Chemistry, and in countries with substantial research investments, including China, the United States, and Germany. Contrary to concerns about a trade-off between quantity and quality, hyperprolific authors tend to produce higher-impact publications on average compared to their peers. Their output is strongly associated with extensive co-authorship networks, reflecting the role of collaboration in enabling prolific publishing. The findings underscore the need for balanced evaluation metrics that prioritize both quality and integrity in academic publishing. This study contributes to understanding the drivers and consequences of hyperprolific behavior, offering insights for research policy and evaluation practices.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101658"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How do academic gatherings promote knowledge production and dissemination?","authors":"Li Hou ,&nbsp;Ruilu Yang","doi":"10.1016/j.joi.2025.101659","DOIUrl":"10.1016/j.joi.2025.101659","url":null,"abstract":"<div><div>Academic gatherings, such as conferences, are one of the most important types of activities in academia, yet they are understudied in the literature. Using a sample of 5379 articles published between 2000 and 2019 in the top five Economics journals, we identify whether the article was presented in academic gatherings based on wording in the paper's Acknowledgement sections, and explore its effect on citations. We find that papers acknowledging academic gatherings are associated with higher citations, and this relationship is mediated by a broader knowledge base and the more attention; that is, acknowledging academic gatherings corresponds to the paper having a broader knowledge base and being viewed more frequently, thus receive higher citations. We also find that papers authored by junior scholars with limited knowledge, skills, and experience benefit more from academic gatherings than those by senior scholars. Our findings deepen the understanding of academic gatherings and knowledge production and dissemination.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101659"},"PeriodicalIF":3.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simple equation for rank-citation profiles","authors":"Y.C. Tay ,&nbsp;Akarsh Srivastava ,&nbsp;Mostafa Rezazad ,&nbsp;Hamid Sarbazi-Azad","doi":"10.1016/j.joi.2025.101660","DOIUrl":"10.1016/j.joi.2025.101660","url":null,"abstract":"<div><div>There is considerable interest in the citation count for an author's publications. This has led to many proposals for citation indices to characterize rank-citation profiles, which order an author's publications by their citation count. However, there is so far no tractable model to facilitate the analysis of these profiles and the design of their indices. This paper presents a simple equation for such design and analysis.</div><div>The equation has three parameters that are calibrated by three geometrical characteristics of a rank-citation profile, namely the maximum number of citations for a publication (<em>M</em>), the number of cited publications (<em>N</em>), and the Hirsch index (<em>h</em>). The equation's simple form makes it tractable for analyzing rank-citation profiles and indices.</div><div>To demonstrate, the equation is used to derive closed-form approximations (in terms of <em>M</em>, <em>N</em> and <em>h</em>) for various indices; these expressions provide new insight into previous index analyses, the influence of a profile's tail, and the effect of time.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101660"},"PeriodicalIF":3.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Researching deeply or broadly? The effects of scientists’ research strategies on disruptive performance over their careers","authors":"Weiyi Ao ,&nbsp;Libo Sheng ,&nbsp;Xuanmin Ruan ,&nbsp;Dongqing Lyu ,&nbsp;Jiang Li ,&nbsp;Ying Cheng","doi":"10.1016/j.joi.2025.101657","DOIUrl":"10.1016/j.joi.2025.101657","url":null,"abstract":"<div><div>The research strategies scientists use can affect the efficiency and direction of scientific discovery. This study focuses on the relationships between scientists’ knowledge breadth and depth strategies and disruptive performance as well as the role career age plays in these relationships. The data were from 651,831 publications authored by 12,278 biomedical scientists from the PubMed Knowledge Graph (PKG) dataset. The two main findings are as follows: (1) U-shaped correlations were found between scientists’ knowledge breadth, depth, and disruptive performance; and (2) career age influences the relationship between knowledge depth and disruptive performance, with different impacts across various stages of a scientist's career. The findings imply that future research must consider the key role scientists’ career age plays in the relationship between research strategies and scientific performance.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101657"},"PeriodicalIF":3.4,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigating disruptions: The effects of the pandemic on scientific collaboration and research novelty in Hong Kong","authors":"Rong Ni ,&nbsp;Jue Wang","doi":"10.1016/j.joi.2025.101656","DOIUrl":"10.1016/j.joi.2025.101656","url":null,"abstract":"<div><div>Scientific collaboration and novelty are fundamental drivers of progress in knowledge advancement and innovation. However, the emergence of the COVID-19 pandemic disrupted traditional channels of scholarly communication, potentially influencing both short- and long-term scientific endeavors. Using data from 116,942 WoS publications from Hong Kong between 2017 and 2022, this study investigates the pandemic's impact on both scientific collaboration and research novelty. Our analysis reveals that the pandemic reduced the proportion of international collaborative papers and led to a contraction in the scale of international collaboration. On the other hand, domestic collaboration increased in both scope and scale. Additionally, while the pandemic negatively affected research novelty, international collaboration significantly mitigated this impact. However, no moderating effect of collaboration was observed on high-novelty research. This study underscores the importance of maintaining a collaborative scientific community and highlights the resilience and adaptability of academic communities when facing unprecedented challenges.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101656"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-agent simulation of team stability evolution: A complexity science perspective","authors":"Liang Yaqi,&nbsp;Hou Guisheng,&nbsp;Jiang Xiujuan","doi":"10.1016/j.joi.2025.101655","DOIUrl":"10.1016/j.joi.2025.101655","url":null,"abstract":"<div><div>Drawing on the theory of complex adaptive systems, this study develops a multi-agent model of a research innovation team through the NetLogo simulation platform. The operational mechanisms of the research innovation team are delineated into three distinct processes: demand-driven collaborative mechanism, objectives-driven knowledge sharing mechanism, and outcome-driven dynamic trust mechanism. These processes describe the individual decision-making of team members and the complex interactions among them. By analyzing the evolutionary patterns of research innovation team stability under various influencing factors, this study shows that: (1) While the effects on team stability vary across different parameter settings, the underlying evolutionary patterns remain largely consistent. (2) The influences of different factors on team stability exhibit nonlinear characteristics. These findings offer theoretical insights and decision-making support for fostering stable development within research innovation teams.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101655"},"PeriodicalIF":3.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The triangle of biomedicine framework to analyze the impact of citations on the dissemination of categories in the PubMed database","authors":"Gerson Pech ,&nbsp;Aleksandra Mreła ,&nbsp;Veslava Osińska ,&nbsp;Oleksandr Sokolov","doi":"10.1016/j.joi.2025.101648","DOIUrl":"10.1016/j.joi.2025.101648","url":null,"abstract":"<div><div>Processing scientific literature metadata allows us to verify the assignment of articles to predefined categories. The Triangle of Biomedicine (TB) is a convenient space for considering the positions of biomedical papers according to human, animal, and molecular-cellular subdisciplines. The placement of PubMed papers in the TB using citations and, what is more interesting, the dynamics of the changing positions of papers (because of citations) have not been examined to date. This research presents a method for finding the article citation vectors of directly cited papers whose components are the MeSH terms shares offered by the PubMed database. The citation vectors allow finding the paper's position in the TB and comparing it with the original position of the publication. The analysis of sets of citation vectors enables locating their position on the translational line to show the distance between human research and animal-molecular studies. Moreover, applying information entropy, the dynamics of entropies in four different sets of articles are studied.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101648"},"PeriodicalIF":3.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New paper-by-paper classification for Scopus based on references reclassified by the origin of the papers citing them","authors":"Jesús M. Álvarez-Llorente ,&nbsp;Vicente P. Guerrero-Bote ,&nbsp;Félix Moya-Anegón","doi":"10.1016/j.joi.2025.101647","DOIUrl":"10.1016/j.joi.2025.101647","url":null,"abstract":"<div><div>A reference-based classification system for individual Scopus publications is presented which takes into account the categories of the papers citing those references instead of the journals in which those cited papers are published. It supports multiple assignments of up to 5 categories within the Scopus ASJC structure, but eliminates the Multidisciplinary Area and the miscellaneous categories, and it allows for the reclassification of a greater number of publications (potentially 100%) than traditional reference-based systems. Twelve variants of the system were obtained by adjusting different parameters, which were applied to the more than 3.2 million citable papers from the active Scientific Journals in 2020 indexed in Scopus. The results were analyzed and compared with other classification systems such as the original journal-based Scopus ASJC, the 2 generation-reference based M3-AWC-0.8 (Álvarez-Llorente et al., 2024), and the corresponding authors' assignment based AAC (Álvarez-Llorente et al., 2023). The different variants obtained of the classification give results that improve those used as references in multiple scientometric fields. The variation called U1-F-0.8 seems especially promising due to its restraint in assigning multiple categories, consistency with reference classifications and the fact of applying normalization processes to avoid the overinfluence of articles that have a greater number of references.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101647"},"PeriodicalIF":3.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequential citation counts prediction enhanced by dynamic contents","authors":"Guoxiu He ,&nbsp;Sichen Gu ,&nbsp;Zhikai Xue ,&nbsp;Yufeng Duan ,&nbsp;Xiaomin Zhu","doi":"10.1016/j.joi.2025.101645","DOIUrl":"10.1016/j.joi.2025.101645","url":null,"abstract":"<div><div>The assessment of the impact of scholarly publications has garnered significant attention among researchers, particularly in predicting the future sequence of citation counts. However, current studies predominantly regard academic papers as static entities, failing to acknowledge the dynamic nature of their fixed content, which can undergo shifts in focus over time. To this end, we implement dynamic representations of the content to mirror chronological changes within the given paper, facilitating the sequential prediction of citation counts. Specifically, we propose a novel deep neural network called <strong>D</strong>ynam<strong>I</strong>c <strong>C</strong>ontent-aware <strong>T</strong>r<strong>A</strong>nsformer (DICTA). The proposed model incorporates a dynamic content module that leverages the power of a sequential module to effectively capture the evolving focus information within each paper. To account for dependencies between the historical and future citation counts, our model utilizes a transformer-based framework as the backbone. With the encoder-decoder structure, it can effectively handle previous citation accumulations and then predict future citation potentials. Extensive experiments conducted on two scientific datasets demonstrate that DICTA achieves impressive performance and outperforms all baseline approaches. Further analyses underscore the significance of the dynamic content module. The code is available: <span><span>https://github.com/ECNU-Text-Computing/DICTA</span><svg><path></path></svg></span></div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101645"},"PeriodicalIF":3.4,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying potential sleeping beauties based on dynamic time warping algorithm and citation curve benchmarking","authors":"Zewen Hu,&nbsp;Yu Chen,&nbsp;Jingjing Cui","doi":"10.1016/j.joi.2025.101646","DOIUrl":"10.1016/j.joi.2025.101646","url":null,"abstract":"<div><div>Sleeping beauty (SB) is recognised as delayed, highly cited, or high-impact literature. The precise and efficient identification of potential sleeping beauties from the massive literature can maximise their value in science and technology development. Therefore, in this study, a new time-series similarity method, called the dynamic time warping (DTW) algorithm, was designed to efficiently identify sleeping beauties. First, the top 1 % of highly cited publications (5423 publications) in the field of Artificial Intelligence (AI) between 1990 and 2010 were identified based on data collected from the Web of Science database. Then, the DTW algorithm was designed and implemented to identify potential sleeping beauties based on the benchmarking sleeping beauty citation curve. Subsequently, the DTW method was combined with three indicators defined by Van Raan (2004) to design the DTW* method. Finally, the newly designed DTW and DTW* methods were used alongside quadratic function fitting (QFF), beauty coefficient (B), and modified beauty coefficient (Bcp) to identify sleeping beauties and evaluate the effect of the DTW algorithm. Among the findings: (1) The DTW algorithm can quickly and effectively identify potential sleeping beauties with help from the citation trajectory of different benchmarking sleeping beauties. These benchmarking sleeping beauties are identified by Raan's criteria from physics, as well as the B and Bcp index from the AI field, indicating the robustness of the DTW method, which is less reliant on methods and disciplinary factors of selecting benchmarking sleeping beauties. The DTW algorithm can automatically and accurately identify different types of highly influential publications, including sleeping beauties and highly cited publications, based on publication citation trajectories, further indicating robustness and application prospects. (2) The DTW* method improves the DTW recognition accuracy using the sleeping time defined by Van Raan, to accurately identify standardised sleeping beauties conforming to the standardised citation curve of benchmarking sleeping beauty, thereby ensuring exclusion of false sleeping beauties with extremely short sleeping time. (3) Using the DTW* method, 39 sleeping beauties with sleeping time greater than five years were identified, among which, 38 met Raan's three criteria with an accuracy of 97 %. Of the 39 sleeping beauties, 62 % were conference publications, suggesting that conference publications have an extremely high probability of becoming a sleeping beauty in the AI field. In content analysis, the 39 sleeping beauties were associated with innovative algorithms, methods, and related applications. (4) The DTW algorithm can be extended to another significant different field as ‘Social Sciences, Interdisciplinary’ category for sleeping beauty identification, further verifying the effectiveness and robustness of the DTW approach.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 2","pages":"Article 101646"},"PeriodicalIF":3.4,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}