Scientometrics最新文献_第7页

Women’s strength in science: exploring the influence of female participation on research impact and innovation 女性在科学领域的力量：探索女性参与对研究影响和创新的影响

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-28 DOI: 10.1007/s11192-024-05089-x

Wenxuan Shi, Renli Wu

{"title":"Women’s strength in science: exploring the influence of female participation on research impact and innovation","authors":"Wenxuan Shi, Renli Wu","doi":"10.1007/s11192-024-05089-x","DOIUrl":"https://doi.org/10.1007/s11192-024-05089-x","url":null,"abstract":"Prevailing attention centers on the plight of female scientists in modern academia. However, female contributions and potential remain insufficiently recognized. To unravel this veil, we leverage large-scale cross-disciplinary datasets from SciSciNet to portray female participation over the past 20 years and quantify the female effect on research using bibliometric indicators. Female ratio is utilized to gauge gender composition within teams. Through successive modeling including mixed-effect and multivariate regressions, we disentangle the intricate effects of female presence and extent of female participation on research impact and dual innovation metrics. We find a steady rise in female-inclusive teams and per-team female ratios over time, with variations across disciplines and broad categories. We demonstrate an inverted U-shaped relationship between female ratio and citation counts—gender-balanced teams typically garner peak citations, while highly-cited vertices drift toward male-skewed teams in male-majority areas. Increasing female participation yields significant gains in innovation. In the upstream of knowledge flow, as captured by novelty (z-scores), female-skewed teams tend to combine more unconventional knowledge. For the downstream, as encapsulated through disruption, female-skewed teams’ innovation efforts have been recognized by follow-on citations. Notably, the female advantage in innovation becomes more evident in male-dominated fields and intensifies over time. Our study offers insights into the unique academic value and the tremendous scientific contributions of females, providing important visions for institutional and policy reforms.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"15 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of datasets citation coverage in Google Scholar, Web of Science, Scopus, Crossref, and DataCite 数据集在 Google Scholar、Web of Science、Scopus、Crossref 和 DataCite 中的引文覆盖率比较

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-28 DOI: 10.1007/s11192-024-05073-5

Irina Gerasimov, Binita KC, Armin Mehrabian, James Acker, Michael P. McGuire

{"title":"Comparison of datasets citation coverage in Google Scholar, Web of Science, Scopus, Crossref, and DataCite","authors":"Irina Gerasimov, Binita KC, Armin Mehrabian, James Acker, Michael P. McGuire","doi":"10.1007/s11192-024-05073-5","DOIUrl":"https://doi.org/10.1007/s11192-024-05073-5","url":null,"abstract":"The rapid increase of Earth science data from remote sensing, models, and ground-based observations highlights an urgent need for effective data management practices. Data repositories track provenance and usage metrics which are crucial for ensuring data integrity and scientific reproducibility. Although the introduction of Digital Object Identifiers (DOIs) for datasets in the late 1990s has significantly aided in crediting creators and enhancing dataset discoverability (akin to traditional research citations), considerable challenges persist in establishing linkage of datasets used with scholarly documents. This study evaluates the citation coverage of datasets from NASA’s Earth Observing System Data and Information System (EOSDIS) across several major bibliographic sources ‒ namely Google Scholar (GS), Web of Science (WoS), Scopus, Crossref, and DataCite—which helps data managers in making informed decisions when selecting bibliographic sources. We provide a robust and comprehensive understanding of the citation landscape, crucial for advancing data management practices and advancing open science. Our study searched and analyzed temporal trends across the bibliographic sources for publications that cite approximately 11,000 DOIs associated with EOSDIS datasets, yielding 17,000 unique journal and conference articles, reports, and book records linked to 3,000 dataset DOIs. GS emerged as the most comprehensive source while Crossref lagged significantly behind the other major sources. Crossref’s record references revealed that the absence of dataset DOIs and shortcomings in the Crossref Event data interface likely contributed to its underperformance. Scopus initially outperformed WoS until 2020, after which WoS began to show superior performance. Overall, our study underscores the necessity of utilizing multiple bibliographic sources for citation analysis, particularly for exploring dataset-to-document connections.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"57 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Co-evolution of international scientific mobility and international collaboration: a Scopus-based analysis 国际科学流动与国际合作的共同演变：基于 Scopus 的分析

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-27 DOI: 10.1007/s11192-024-05081-5

Ruimin Pei, Langqiu Li, Yiying Yang, Quan Zhou

{"title":"Co-evolution of international scientific mobility and international collaboration: a Scopus-based analysis","authors":"Ruimin Pei, Langqiu Li, Yiying Yang, Quan Zhou","doi":"10.1007/s11192-024-05081-5","DOIUrl":"https://doi.org/10.1007/s11192-024-05081-5","url":null,"abstract":"Science and technology human resources are fundamental components for enhancing the efficiency of the national innovation system. This study aims to examine the co-evolutionary relationship between scientific collaboration and scientific mobility, explore the dynamic development process of collaboration and talent flow within the global science system, and offer insights for developing suitable policies related to scientific mobility and international collaboration. The study employs Scopus data from 1788 to 2020 to investigate the systematic co-evolution of scientific talent flow and scientific collaboration from a macro and long-term perspective. The findings indicate that: (1) The global scientific flow and collaboration networks are increasingly interconnected, with a rising prevalence of international mobility and intensified worldwide collaboration. (2) Both networks exhibit cluster structures that have evolved over time, with a shift towards more random network configurations, reflecting more extensive and frequent global scientific interactions. (3) The “Matthew Effect” is observed, highlighting an imbalance with a few dominant players and many minor participants, while advanced countries demonstrate greater alignment between collaboration and mobility networks than lagging ones. Policy implications include encouraging international research mobility, supporting cooperation within scientific clusters, and prioritizing connections with global research hubs while engaging with peripheral countries.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"356 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Policy citations of scientometric articles: an altmetric study 科学计量学文章的政策引文：一项 altmetric 研究

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-27 DOI: 10.1007/s11192-024-05091-3

Hashem Atapour, Robabeh Maddahi, Rasoul Zavaraqi

{"title":"Policy citations of scientometric articles: an altmetric study","authors":"Hashem Atapour, Robabeh Maddahi, Rasoul Zavaraqi","doi":"10.1007/s11192-024-05091-3","DOIUrl":"https://doi.org/10.1007/s11192-024-05091-3","url":null,"abstract":"Policy citations are considered as one of the important indicators of the societal impact of research. Scientometrics is a field that, among other goals, focus on contributing to science policy, so the presence of scientometric researches in policy documents become important. Accordingly, this study aims to measure the impact of scientometric researches on policy by examining the mentions of scientometric articles in policy documents. The dataset used in this study includes 5525 scientometric articles indexed in Web of Science between 2013 and 2022. The Overton database were used to collect policy citations. The results showed that out of 5525 scientometric articles, 921 articles (16.67%) were cited at least once in policy documents. Additionally, older articles were cited more frequently than recent ones in policy documents. Scientometrics Journal ranked first in terms of the number of articles being cited in policy documents, while Research Policy and Research Evaluation Journals ranked first and second, respectively, in terms of coverage, density, and intensity. Subject analysis of the cited articles in policy documents showed that articles on national/international scholar collaborations, scholar productivity/scholar performance, and funding and sponsorship were cited more frequently in policy documents. Finally, Open Access articles were cited more frequently than non-open access articles in policy documents. However, there was not significant difference between policy citations of multi-authored and sing-authored articles. Overall, policy citations of scientometric articles were fair compared to other fields, and for greater impact of this field on policy, publishing open access, and greater attention to the topics identified in this study can be helpful.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"1 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gender of gender studies: examining regional and gender-based disparities in scholarly publications 性别研究中的性别问题：审查学术出版物中的地区和性别差异

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-27 DOI: 10.1007/s11192-024-05084-2

Arjun Prakash, Jeevan John Varghese, Shruti Aggarwal

{"title":"Gender of gender studies: examining regional and gender-based disparities in scholarly publications","authors":"Arjun Prakash, Jeevan John Varghese, Shruti Aggarwal","doi":"10.1007/s11192-024-05084-2","DOIUrl":"https://doi.org/10.1007/s11192-024-05084-2","url":null,"abstract":"This study comprehensively analyses gender representation and citation disparities in gender studies by examining the position of female scholars as first and corresponding authors. The research uncovers a pattern of gender-homogeneous co-authorship and investigates the geographical and economic disparities in academic contributions, scrutinising the impact of a country’s economic status on citation rates and open-access publications, particularly in relation to citation rates and open-access publications. The study uses a Logistics Regression and Zero-Inflated Negative Binomial Regression model to explore factors influencing open-access publication and citation rates. The study’s findings demonstrate the predominant presence of female scholars in gender-focused literature within social sciences, in contrast to their underrepresentation in STEM fields. The findings also reveal a tendency towards gender-homogenous collaborations and a significant concentration of scholarly output from the high-income regions, highlighting both geographic and economic disparities. The present study provides an analytical foundation for future studies on the global distribution of scholarly contributions and the complex interplay of various factors affecting academic publishing in gender studies.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"23 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Citation advantage of positive words: predictability, temporal evolution, and universality in varied quality journals 正面词语的引用优势：不同质量期刊的可预测性、时间演变和普遍性

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-27 DOI: 10.1007/s11192-024-05074-4

Dengsheng Wu, Huidong Wu, Jianping Li

{"title":"Citation advantage of positive words: predictability, temporal evolution, and universality in varied quality journals","authors":"Dengsheng Wu, Huidong Wu, Jianping Li","doi":"10.1007/s11192-024-05074-4","DOIUrl":"https://doi.org/10.1007/s11192-024-05074-4","url":null,"abstract":"The number of positive words in scientific papers has exhibited a notable upwards trend over the past few decades. However, there remains a gap in our comprehensive understanding of the relationship between positive words and research impact. In this study, we conduct a multifaceted exploration of the citation advantage associated with positive words based on social cognitive theory, examining its predictability, temporal evolution, and universality across journals of varying quality grades. Drawing from a corpus encompassing 124,144 papers published in the management field between 2001 and 2020, our regression results provide compelling evidence suggesting that positive words can serve as a significant predictor of the citation counts of academic papers, supporting the citation advantage of positive words. However, it is essential to recognize that over time, the citation advantage attributed to positive words is experiencing a conspicuous decline. The universality of the above phenomenon has been further verified in the analysis of journals of different quality. Our findings prompt a discussion regarding the need to pay more attention to the overuse and misuse of positive words, as well as practical considerations for enhancing scientific communication within the academic community.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"38 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multilateral co-authorship: an important but easily overlooked pattern in international scientific collaboration research 多边共同著作：国际科学合作研究中一个重要但容易被忽视的模式

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-27 DOI: 10.1007/s11192-024-05095-z

Weishu Liu, Ruifeng Zhang

引用次数: 0

A validation test of the Uzzi et al. novelty measure of innovation and applications to collaboration patterns between institutions 对 Uzzi 等人的创新新颖性衡量标准进行验证测试，并将其应用于机构间的合作模式

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-27 DOI: 10.1007/s11192-024-05071-7

Yuefen Wang, Lipeng Fan, Lei Wu

{"title":"A validation test of the Uzzi et al. novelty measure of innovation and applications to collaboration patterns between institutions","authors":"Yuefen Wang, Lipeng Fan, Lei Wu","doi":"10.1007/s11192-024-05071-7","DOIUrl":"https://doi.org/10.1007/s11192-024-05071-7","url":null,"abstract":"Exploring a robust and universal appeal bibliometric indicator for assessing creativity is essential but challenging. The novelty measure of innovation proposed by Uzzi et al. (NoveltyU) has sparked considerable interest and debate. Thus, further validation and understanding of its portfolio form of novelty and scope of application are necessary. This paper delves into the calculation and application of the NoveltyU method to shed light on its effectiveness and scope. Analysis of the calculation process reveals that journal pairs with higher novelty often span independent fundamental areas, while those with lower novelty tend to focus on similar and applied fields. Utilizing collaboration patterns between institutions, as discussed in our prior study (Fan et al., Scientometrics 125:1179–1196, 2020), offers insight into the method’s performance in real-world contexts. Results consistently show higher mean NoveltyU values in MM pattern over time, affirming the method’s validity. Categorizing papers into high conventional, low conventional, low novel, and high novel categories unveils higher overlap degree of terms among different patterns in high novel papers. Moreover, leading terms in MM pattern exhibit specific information, while delay terms tend to be more general, and simultaneous terms are even more so. These findings offer valuable insights into identifying hot and frontier topics, bolstering the credibility and application potential of the NoveltyU method, aligning with the broader objective of establishing valid measures of innovativeness in research.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"24 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Is Management and Organizational Studies divided into (micro-)tribes? 管理与组织研究是否分为（微）部落？

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-25 DOI: 10.1007/s11192-024-05013-3

Oliver Wieczorek, Olof Hallonsten, Fredrik Åström

引用次数: 0

Predicting citation impact of academic papers across research areas using multiple models and early citations 利用多种模型和早期引文预测各研究领域学术论文的引文影响力

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-25 DOI: 10.1007/s11192-024-05086-0

Fang Zhang, Shengli Wu

{"title":"Predicting citation impact of academic papers across research areas using multiple models and early citations","authors":"Fang Zhang, Shengli Wu","doi":"10.1007/s11192-024-05086-0","DOIUrl":"https://doi.org/10.1007/s11192-024-05086-0","url":null,"abstract":"As the volume of scientific literature expands rapidly, accurately gauging and predicting the citation impact of academic papers has become increasingly imperative. Citation counts serve as a widely adopted metric for this purpose. While numerous researchers have explored techniques for projecting papers’ citation counts, a prevalent constraint lies in the utilization of a singular model across all papers within a dataset. This universal approach, suitable for small, homogeneous collections, proves less effective for large, heterogeneous collections spanning various research domains, thereby curtailing the practical utility of these methodologies. In this study, we propose a pioneering methodology that deploys multiple models tailored to distinct research domains and integrates early citation data. Our approach encompasses instance-based learning techniques to categorize papers into different research domains and distinct prediction models trained on early citation counts for papers within each domain. We assessed our methodology using two extensive datasets sourced from DBLP and arXiv. Our experimental findings affirm that the proposed classification methodology is both precise and efficient in classifying papers into research domains. Furthermore, the proposed prediction methodology, harnessing multiple domain-specific models and early citations, surpasses four state-of-the-art baseline methods in most instances, substantially enhancing the accuracy of citation impact predictions for diverse collections of academic papers.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"149 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0