Scientometrics最新文献_第9页

Collaboration at the phylum level: coauthorship and acknowledgment patterns in the world of the water bears (phylum Tardigrada) 动物门一级的合作：水熊（动物门）世界中的共同著作和鸣谢模式

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-20 DOI: 10.1007/s11192-024-05036-w

Katherine W. McCain

{"title":"Collaboration at the phylum level: coauthorship and acknowledgment patterns in the world of the water bears (phylum Tardigrada)","authors":"Katherine W. McCain","doi":"10.1007/s11192-024-05036-w","DOIUrl":"https://doi.org/10.1007/s11192-024-05036-w","url":null,"abstract":"Coauthor and acknowledgment data were captured for 1384 research articles published between 1980 and June, 2023 that focused on tardigrades. Articles indexed in Web of Science or an archives of tardigrade literature were downloaded and thoroughly examined for personal acknowledgment data. Annual publication counts and coauthor maps for four successive time periods (1980–1999, 2000–2008, 2009–2017, 2018-June 2023) showed growth in the literature and increased research activity (more researchers, more complex networks, more international collaboration), beginning in 2000. A two-level Personal Acknowledgments Classification (PAC), was used to code types of acknowledgments. The majority of articles focused on field studies and/or descriptions of new species of tardigrades. This was reflected in rankings of acknowledgment categories and additions to the PAC. Ranked lists of frequently-thanked acknowledgees (all tardigrade researchers) were produced for each period. Acknowledgment profiles of four frequently-thanked researchers identified three different roles that researchers might play in tardigrade studies—”informal academic editorial consultant,” “taxonomic gatekeeper,” and “all-rounder.” Acknowledgments honoring people by naming a new species after them were only found in the species description, not in the formal acknowledgment section.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"63 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141524268","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

Degree assortativity in collaboration networks and breakthrough innovation: the moderating role of knowledge networks 合作网络中的程度同类性与突破性创新：知识网络的调节作用

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-08 DOI: 10.1007/s11192-024-05063-7

Runhui Lin, Biting Li, Yanhong Lu, Yalin Li

{"title":"Degree assortativity in collaboration networks and breakthrough innovation: the moderating role of knowledge networks","authors":"Runhui Lin, Biting Li, Yanhong Lu, Yalin Li","doi":"10.1007/s11192-024-05063-7","DOIUrl":"https://doi.org/10.1007/s11192-024-05063-7","url":null,"abstract":"Collaboration networks are widely recognized as essential channels for accessing innovation resources and facilitating creative activities by enabling the exchange of knowledge and information. However, there is little known about whether and how the similarities and dissimilarities between actors forming ties in a collaboration network can either stimulate or inhibit firms’ breakthrough innovation. This study explores the relationship between degree assortativity in collaboration networks and breakthrough innovation performance, considering the moderating role of knowledge network characteristics. Using a sample of 80,129 semiconductor patents from the United States Patent and Trademark Office database spanning the years 1975 to 2007, we constructed both the internal collaboration network and the knowledge network of firms. To test our hypotheses, we employed a negative binomial regression model. Our findings demonstrate that firms with lower degree assortativity in their collaboration networks tend to exhibit higher levels of breakthrough innovation performance compared to those with higher degree assortativity. Moreover, the number of direct ties in the knowledge network strengthens the negative relationship between collaboration network degree assortativity and breakthrough innovation. Conversely, the number of non-redundant ties in the knowledge network mitigates the negative relationship between collaboration network degree assortativity and breakthrough innovation. This study provides practical guidance for firms aiming to enhance their innovation capabilities by simultaneously developing internal collaboration networks and knowledge networks.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"24 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504467","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

Streetlight effect in PubPeer comments: are Open Access publications more scrutinized? PubPeer 评论中的路灯效应：开放获取出版物是否受到更严格的审查？

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-04 DOI: 10.1007/s11192-024-05053-9

Abdelghani Maddi, Emmanuel Monneau, Catherine Guaspare-Cartron, Floriana Gargiulo, Michel Dubois

{"title":"Streetlight effect in PubPeer comments: are Open Access publications more scrutinized?","authors":"Abdelghani Maddi, Emmanuel Monneau, Catherine Guaspare-Cartron, Floriana Gargiulo, Michel Dubois","doi":"10.1007/s11192-024-05053-9","DOIUrl":"https://doi.org/10.1007/s11192-024-05053-9","url":null,"abstract":"The Streetlight Effect represents an observation bias that occurs when individuals search for something only where it is easiest to look. Despite the significant development of Post-Publication Peer Review (PPPR) in recent years, facilitated in part by platforms such as PubPeer, existing literature has not examined whether PPPR is affected by this type of bias. In other words, if the PPPR mainly concerns publications to which researchers have direct access (eg to analyze image duplications, etc.). In this study, we compare the Open Access (OA) structures of publishers and journals among 51,882 publications commented on PubPeer to those indexed in OpenAlex database (#156,700,177). Our findings indicate that OA journals are 33% more prevalent in PubPeer than in the global total (52% for the most commented journals). This result can be attributed to disciplinary bias in PubPeer, with overrepresentation of medical and biological research (which exhibits higher levels of openness). However, after normalization, the results reveal that PPPR does not exhibit a Streetlight Effect, as OA publications, within the same discipline, are on average 16% less prevalent in PubPeer than in the global total. These results suggest that the process of scientific self-correction operates independently of publication access status.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"5 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141253303","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

Towards a new approach to analyzing the geographical scope of national research. An exploratory analysis at the country level 采用新方法分析国家研究的地理范围。国家层面的探索性分析

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-03 DOI: 10.1007/s11192-024-05045-9

Sandra Miguel, Claudia M. González, Zaida Chinchilla-Rodríguez

引用次数: 0

Altmetric data quality analysis using Benford’s law 使用本福德定律分析 Altmetric 数据质量

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-03 DOI: 10.1007/s11192-024-05061-9

Solanki Gupta, Vivek Kumar Singh, Sumit Kumar Banshal

{"title":"Altmetric data quality analysis using Benford’s law","authors":"Solanki Gupta, Vivek Kumar Singh, Sumit Kumar Banshal","doi":"10.1007/s11192-024-05061-9","DOIUrl":"https://doi.org/10.1007/s11192-024-05061-9","url":null,"abstract":"Altmetrics, or alternative metrics, refer to the newer kind of events around scholarly articles, such as the number of times the article is read, tweeted, mentioned in blog posts etc. These metrics have gained a lot of popularity during last few years and are now being collected and used in several ways, ranging from early measure of article impact to a potential indicator of societal relevance of research. However, there are several studies which have cautioned about use of altmetrics on account of quality and reliability of altmetric data, as they may be more prone to manipulations and artificial inflations. This study proposes a framework based on application of Benford’s Law to evaluate the quality of altmetric data. A large sized altmetric data sample is considered and the fits with Benford’s Law are computed. The analysis is performed by doing plots of the empirical data distributions and the theoretical Benford's, and by employing relevant statistical measures and tests. Results for fit on first and second leading digit of altmetric data show conformity to Benford's distribution. To further explore the usefulness of the framework, the altmetric data is subjected to artificial manipulations through a systematic process and the fits to Benford’s law are reassessed to see if there are distortions. The results and analysis suggest that Benford’s Law based framework can be used to test the quality of altmetric data. Relevant implications of the research are discussed.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"4 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141253299","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

A decadal study on identifying latent topics and research trends in open access LIS journals using topic modeling approach 利用主题建模方法识别开放获取的 LIS 期刊中的潜在主题和研究趋势的十年期研究

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-06-03 DOI: 10.1007/s11192-024-05058-4

Abhijit Thakuria, Dipen Deka

{"title":"A decadal study on identifying latent topics and research trends in open access LIS journals using topic modeling approach","authors":"Abhijit Thakuria, Dipen Deka","doi":"10.1007/s11192-024-05058-4","DOIUrl":"https://doi.org/10.1007/s11192-024-05058-4","url":null,"abstract":"The study utilized Latent Dirichlet Allocation (LDA) Topic modeling to identify prevalent latent topics within Open Access (OA) Library and Information Science (LIS) journals from 2013 to 2022. Eight core OA Scopus indexed journals were selected based on their SJR scores and DOAJ listing. Titles, Abstracts and keywords of 2589 articles were extracted from the Scopus database. R software packages were used to perform data analysis and LDA topic modeling. The optimal value of k was determined to be 9. The analysis revealed that 53.89% of documents comprise over 50% of a certain topic (θ > 0.50). Notably, ‘Scholarly Communication’ and ‘Information Systems, Models and Frameworks’ emerged as dominant topics with the highest proportions of research literature in the corpus. The topic ‘Scholarly Communication’ experienced significant growth with an average annual growth rate (AAGR) of 4.37%, while ‘Collection development and E-resources’ exhibited the lowest research proportion and a negative AAGR of − 4.22%. Additionally, topics such as ‘Information Seeking Behaviour and User Studies’, ‘User Education and Information Literacy’, and ‘Information Retrieval and Systematic Review’ remained stable and persistent topics. Conversely, research on traditional topics like ‘Librarianship and Profession’, ‘Bibliometrics’ and ‘Medical Library and Health Information’ showed a gradual decline. The LDA topic modeling approach unveiled previously unknown or unexplored topics in open access LIS research literature, enhancing our understanding of emerging trends.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"126 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141253093","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

On weighted two-mode network projections 关于加权双模式网络投影

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-05-28 DOI: 10.1007/s11192-024-05041-z

Vladimir Batagelj

引用次数: 0

Research funding in the Middle East and North Africa: analyses of acknowledgments in scientific publications indexed in the Web of Science (2008–2021) 中东和北非的研究经费：分析科学网收录的科学出版物中的致谢（2008-2021 年）

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-05-28 DOI: 10.1007/s11192-024-04983-8

Jamal El-Ouahi

{"title":"Research funding in the Middle East and North Africa: analyses of acknowledgments in scientific publications indexed in the Web of Science (2008–2021)","authors":"Jamal El-Ouahi","doi":"10.1007/s11192-024-04983-8","DOIUrl":"https://doi.org/10.1007/s11192-024-04983-8","url":null,"abstract":"Funding acknowledgments are important objects of study in the context of science funding. This study uses a mixed-methods approach to analyze the funding acknowledgments found in 2.3 million scientific publications published between 2008 and 2021 by authors affiliated with research institutions in the Middle East and North Africa (MENA). The aim is to identify the major funders, assess their contribution to national scientific publications, and gain insights into the funding mechanism in relation to collaboration and publication. Publication data from the Web of Science is examined to provide key insights about funding activities. Saudi Arabia and Qatar lead the region, as about half of their publications include acknowledgments to funding sources. Most MENA countries exhibit strong linkages with foreign agencies, mainly due to a high level of international collaboration. The distinction between domestic and international publications reveals some differences in terms of funding structures. For instance, Turkey and Iran are dominated by one or two major funders whereas a few other countries like Saudi Arabia showcase multiple funders. Iran and Kuwait are examples of countries where research is mainly funded by domestic funders. The government and academic sectors mainly fund scientific research in MENA whereas the industry sector plays little or no role in terms of research funding. Lastly, the qualitative analyses provide more context into the complex funding mechanism. The findings of this study contribute to a better understanding of the funding structure in MENA countries and provide insights to funders and research managers to evaluate the funding landscape.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"43 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141170097","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

The scientometrics and reciprocality underlying co-authorship panels in Google Scholar profiles 谷歌学术档案中共同作者面板所蕴含的科学计量学和互惠性

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-05-27 DOI: 10.1007/s11192-024-05026-y

Ariel Alexi, Teddy Lazebnik, Ariel Rosenfeld

引用次数: 0

Extracting problem and method sentence from scientific papers: a context-enhanced transformer using formulaic expression desensitization 从科学论文中提取问题句和方法句：使用公式化表达脱敏的语境增强转换器

IF 3.9 3区管理学

Scientometrics Pub Date : 2024-05-27 DOI: 10.1007/s11192-024-05048-6

Yingyi Zhang, Chengzhi Zhang

{"title":"Extracting problem and method sentence from scientific papers: a context-enhanced transformer using formulaic expression desensitization","authors":"Yingyi Zhang, Chengzhi Zhang","doi":"10.1007/s11192-024-05048-6","DOIUrl":"https://doi.org/10.1007/s11192-024-05048-6","url":null,"abstract":"Billions of scientific papers lead to the need to identify essential parts from the massive text. Scientific research is an activity from putting forward problems to using methods. To learn the main idea from scientific papers, we focus on extracting problem and method sentences. Annotating sentences within scientific papers is labor-intensive, resulting in small-scale datasets that limit the amount of information models can learn. This limited information leads models to rely heavily on specific forms, which in turn reduces their generalization capabilities. This paper addresses the problems caused by small-scale datasets from three perspectives: increasing dataset scale, reducing dependence on specific forms, and enriching the information within sentences. To implement the first two ideas, we introduce the concept of formulaic expression (FE) desensitization and propose FE desensitization-based data augmenters to generate synthetic data and reduce models’ reliance on FEs. For the third idea, we propose a context-enhanced transformer that utilizes context to measure the importance of words in target sentences and to reduce noise in the context. Furthermore, this paper conducts experiments using large language model (LLM) based in-context learning (ICL) methods. Quantitative and qualitative experiments demonstrate that our proposed models achieve a higher macro F1 score compared to the baseline models on two scientific paper datasets, with improvements of 3.71% and 2.67%, respectively. The LLM based ICL methods are found to be not suitable for the task of problem and method extraction.","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"65 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141170098","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