Journal of Informetrics最新文献_第8页

Analysis of the distribution of authorship by gender in scientific output: A global perspective 分析科学成果中作者的性别分布：全球视角

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-07-05 DOI: 10.1016/j.joi.2024.101556

Rodrigo Sánchez-Jiménez , Pablo Guerrero-Castillo , Vicente P. Guerrero-Bote , Gali Halevi , Félix De-Moya-Anegón

{"title":"Analysis of the distribution of authorship by gender in scientific output: A global perspective","authors":"Rodrigo Sánchez-Jiménez , Pablo Guerrero-Castillo , Vicente P. Guerrero-Bote , Gali Halevi , Félix De-Moya-Anegón","doi":"10.1016/j.joi.2024.101556","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101556","url":null,"abstract":"<div><p>This study presents a thorough examination of gendered scholarly contributions and impact from 2003 to 2023, encompassing details on 212,631,585 authorships indexed in Scopus. The analysis unveils promising advancements towards gender equity, demonstrating an increase in contributions from both genders, which indicates the trend towards a progressive and inclusive environment. These findings challenge an initial perception of male prolificacy. The positive trends extend to female-led research teams, highlighting a correlation between gender balance and leadership. This evolving landscape is reflected in the convergence of male and female authorship participation over time. A decline in citable papers suggests a narrowing of the productivity gap, which challenges gender disparities in impact metrics and emphasizes the multifaceted nature of scholarly excellence across genders. Our data and gender classification method also enables us to look into the country level in order to characterize gender distribution locally. Contrary to conventional assumptions, developing countries are exhibiting a pronounced evolution in female authorship rates. In summary, the study underscores the positive trends towards gender equity, advocating for sustained efforts to promote diversity and foster nuanced understanding in academia.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 3","pages":"Article 101556"},"PeriodicalIF":3.4,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1751157724000695/pdfft?md5=16278f163d9d6d507d87c556fe754937&pid=1-s2.0-S1751157724000695-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141542377","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}

引用次数: 0

A recommendation approach of scientific non-patent literature on the basis of heterogeneous information network 基于异构信息网络的科学非专利文献推荐方法

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-06-29 DOI: 10.1016/j.joi.2024.101557

Shuo Xu , Xinyi Ma , Hong Wang , Xin An , Ling Li

{"title":"A recommendation approach of scientific non-patent literature on the basis of heterogeneous information network","authors":"Shuo Xu , Xinyi Ma , Hong Wang , Xin An , Ling Li","doi":"10.1016/j.joi.2024.101557","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101557","url":null,"abstract":"<div><p>In the procedure of exploring science-technology linkages, <em>non-patent literature</em> (NPL) in patents, particularly scientific NPL, is considered to signal the relatedness between the developed technology and the cited science. However, many prior art search tools may not be powered with the cross-collection recommendation technique, or have limited cross-collection recommendation capabilities. In this paper, we present an approach to recommend scientific NPL for a focal patent on the basis of heterogeneous information network. This study views this cross-collection recommendation problem as a link prediction problem on the basis of meta-path counting approach. Extensive experiments on DrugBank dataset in the pharmaceutical field indicate that our approach is feasible and effective. This work provides a novel perspective on scientific NPL recommendation for a focal patent and opens up further possibilities for the linkages between science and technology. Nevertheless, more experiments in other fields are required to verify the recommended effects of the approach proposed in this study.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101557"},"PeriodicalIF":3.4,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141482020","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}

引用次数: 0

Networks and their degree distribution, leading to a new concept of small worlds 网络及其程度分布，引出小世界的新概念

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-06-25 DOI: 10.1016/j.joi.2024.101554

Leo Egghe

引用次数: 0

Development and application of a comprehensive glossary for the identification of statistical and methodological concepts in peer review reports 编制和应用综合词汇表，以确定同行评审报告中的统计和方法概念

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-06-24 DOI: 10.1016/j.joi.2024.101555

Ivan Buljan , Daniel Garcia-Costa , Francisco Grimaldo , Richard A. Klein , Marjan Bakker , Ana Marušić

{"title":"Development and application of a comprehensive glossary for the identification of statistical and methodological concepts in peer review reports","authors":"Ivan Buljan , Daniel Garcia-Costa , Francisco Grimaldo , Richard A. Klein , Marjan Bakker , Ana Marušić","doi":"10.1016/j.joi.2024.101555","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101555","url":null,"abstract":"<div><p>The assessment of problems identified by peer researchers during peer review is difficult because the content of these reports is typically confidential. The current study sought to construct and apply a glossary for the identification of methodological and statistical concepts mentioned in peer review reports. Three assessors created a list of 1,036 different terms in 19 categories. The glossary was tested on the confidential PEERE database, a sample of 496,928 peer review reports from various scientific disciplines. The most frequently mentioned terms were related to data presentation (found in 40.3 % of the reports) and parametric descriptive statistics (33.3 %). Review reports suggesting a rejection were more likely to mention methodological issues, whereas statistical issues were raised more frequently in review reports recommending revisions. Across disciplines, methodological issues were more frequently mentioned in social sciences (64.1 %), while health and medical sciences were more predictive for the identification of statistical issues (40.1 %). Female reviewers identified more statistical issues compared to male reviewers. These results indicate that the glossary could be used as an additional tool for the assessment of the content of peer review reports and for understanding what help authors may need in writing research articles.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 3","pages":"Article 101555"},"PeriodicalIF":3.4,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141479799","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}

引用次数: 0

How do network embeddedness and knowledge stock influence collaboration dynamics? Evidence from patents 网络嵌入性和知识存量如何影响合作动态？来自专利的证据

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-06-18 DOI: 10.1016/j.joi.2024.101553

Qianqian Jin , Hongshu Chen , Xuefeng Wang , Fei Xiong

{"title":"How do network embeddedness and knowledge stock influence collaboration dynamics? Evidence from patents","authors":"Qianqian Jin , Hongshu Chen , Xuefeng Wang , Fei Xiong","doi":"10.1016/j.joi.2024.101553","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101553","url":null,"abstract":"<div><p>Science, technology, and innovation are becoming increasingly collaborative, prompting concerted efforts to understand and measure the factors influencing these collaborations. This study aims to explore the driving factors and underlying mechanisms of collaboration dynamics based on patent data. Multilayer longitudinal networks are constructed to scrutinize interactions among organizations as well as the embedding of their knowledge elements in the network fabric. We then analyze the structures and characteristics of collaboration and knowledge networks from global and local perspectives, in which process topological indicators and graphlets are used to feature each organization's collaborative patterns and knowledge stock. Knowledge elements are extracted to present the core concepts of patents, overcoming the limitations of predefined categorizations, such as IPC, when representing technological content and context. By performing a longitudinal analysis using a stochastic actor-oriented model, we integrate network structures, node characteristics, and different dimensions of proximity to model collaboration dynamics and reveal the driving factors behind them. An empirical study in the field of lithography finds that organizations with a larger number of partners or a higher number of annular graphlets in their collaboration networks are less likely to collaborate with others. If an assignee has a more extensive range of knowledge elements and demonstrates a higher capability for knowledge combination, or if its local knowledge network exhibits weaker connectivity, its propensity to seek new collaborators increases. Both cognitive and organizational proximity play important roles in fostering collaboration.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101553"},"PeriodicalIF":3.7,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424065","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}

引用次数: 0

Overcoming recognition delays in disruptive research: The impact of team size, familiarity, and reputation 克服颠覆性研究中的识别延迟：团队规模、熟悉程度和声誉的影响

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-06-13 DOI: 10.1016/j.joi.2024.101549

Huihuang Jiang , Jianlin Zhou , Yiming Ding , An Zeng

{"title":"Overcoming recognition delays in disruptive research: The impact of team size, familiarity, and reputation","authors":"Huihuang Jiang , Jianlin Zhou , Yiming Ding , An Zeng","doi":"10.1016/j.joi.2024.101549","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101549","url":null,"abstract":"<div><p>The relationship between disruption and delayed recognition is a critical research topic, yet the connection between the degree of disruption and delayed acknowledgment remains unclear. This study investigates the extent of recognition delay for disruptive papers using the SciSciNet dataset. We conducted a quantitative analysis based on this extensive dataset to examine the relationship between the Disruption Index and the Sleeping Beauty Index, revealing that highly disruptive papers often face a latency period before gaining acknowledgment, with significant variations across disciplines and over time. Our analysis of team dynamics indicates that larger teams, the presence of high-impact authors, fixed teams, and hierarchically structured teams can significantly reduce this delay. These findings provide insights into optimizing team strategies and understanding the complexities of academic recognition. They offer valuable implications for researchers and policymakers aiming to foster and accelerate the acknowledgment of groundbreaking scientific contributions.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101549"},"PeriodicalIF":3.7,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141322785","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}

引用次数: 0

A co-citation approach to the analysis on the interaction between scientific and technological knowledge 以共同引用的方式分析科学知识与技术知识之间的相互作用

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-06-10 DOI: 10.1016/j.joi.2024.101548

Xi Chen , Jin Mao , Gang Li

{"title":"A co-citation approach to the analysis on the interaction between scientific and technological knowledge","authors":"Xi Chen , Jin Mao , Gang Li","doi":"10.1016/j.joi.2024.101548","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101548","url":null,"abstract":"<div><p>A systematic understanding of the interaction between science and technology is beneficial for innovation policies aimed at improving the utilization of science to advance technological development. Traditional approaches primarily focus on direct citation-based linkages, often overlooking the complex, evolving nature of the interaction between scientific and technological knowledge (S&T knowledge interaction). To address this issue, we proposed a novel methodological framework utilizing co-citations between patents and papers, offering a more comprehensive insight into the S&T knowledge interaction. First, we measured the linkage between scientific and technological knowledge based on co-citations between patents and papers. Then, we identified interaction communities and analyzed their evolution. This method not only captures the potential linkages between patents and papers, but also reveals consolidated interactions and rapid changes in S&T knowledge interaction. The results highlight distinct phases in the evolution of S&T knowledge interaction, which are instrumental for understanding how S&T knowledge interaction evolve, especially in rapidly advancing fields like genetic engineering. The insights gained are crucial for academics and practitioners in anticipating future trends and navigating the evolving landscape of science and technology.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 3","pages":"Article 101548"},"PeriodicalIF":3.7,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141303429","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}

引用次数: 0

How the readability of manuscript before journal submission advantages peer review process: Evidence from biomedical scientific publications 期刊投稿前稿件的可读性对同行评审过程有何益处？生物医学科学出版物的证据

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-06-08 DOI: 10.1016/j.joi.2024.101547

Zhuanlan Sun , Dongjin He , Yiwei Li

{"title":"How the readability of manuscript before journal submission advantages peer review process: Evidence from biomedical scientific publications","authors":"Zhuanlan Sun , Dongjin He , Yiwei Li","doi":"10.1016/j.joi.2024.101547","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101547","url":null,"abstract":"<div><p>The practice of uploading preprints of scientific manuscripts prior to journal submission has become increasingly popular. As such, it is essential to understand the impact of the preprint version of a manuscript on the peer review process to facilitate the development of open peer review practices. In the current research, we analyze a dataset comprising 1,078 biomedical papers published in <em>Nature Communications</em> and <em>eLife</em> in 2019, along with their manuscript information posted on preprint servers and their peer review histories. Our investigation focuses on the relationship between the readability of manuscript before journal submission, as represented by preprints, and the sentimental features expressed by reviewers. Based on empirical analysis utilizing a linear regression model, it has been found that reviewers are inclined to express positive sentiments towards preprints characterized by technical language, as indicated by low value on the readability indices. Additional subgroup analysis suggests that this positive effect is more pronounced in papers with lower social and scientific impact, as indicated by online attention scores and scholarly views after publication, respectively. Overall, results of our analysis reveals that the utilization of technical language characterized by lower readability level in academic papers does not seem to hinder the peer review process in biomedical science, which has significant implications for the open peer review practice.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 3","pages":"Article 101547"},"PeriodicalIF":3.7,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141294435","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}

引用次数: 0

Exploring motivations for algorithm mention in the domain of natural language processing: A deep learning approach 探索自然语言处理领域提及算法的动机：深度学习方法

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-06-08 DOI: 10.1016/j.joi.2024.101550

Yuzhuo Wang , Yi Xiang , Chengzhi Zhang

{"title":"Exploring motivations for algorithm mention in the domain of natural language processing: A deep learning approach","authors":"Yuzhuo Wang , Yi Xiang , Chengzhi Zhang","doi":"10.1016/j.joi.2024.101550","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101550","url":null,"abstract":"<div><p>With the formation of the fourth paradigm of scientific research, algorithms have become increasingly important in scientific research. In academic papers, algorithms may be mentioned by scholars with various motivations, using, comparing, or improving algorithms to solve complex research tasks. Identifying these motivations can help scholars discover the relationships between algorithms and further assess their roles and values. Therefore, taking the field of natural language processing (NLP) as an example, this article proposes a complete method to conduct the identification, distribution, and evolution of motivations for mentioning algorithms at the sentence level. Specifically, using manual annotation and machine learning methods, we identify algorithm entities and sentences in the full text of papers, classify motivations for mentioning algorithms by pre-training models and data augmentation techniques, and finally analyze the distribution and evolution of motivations. The results show that the deep learning models trained with the augmented data outperform the traditional machine learning models in the classification task. In academic papers, more than half of the sentences show the direct use of algorithms, while the lowest percentage of motivations are improving algorithms, and the diversity of motivations has been increasing with time. For specific algorithms, grammatical algorithms are mentioned more by the motivation of “description,” while more motivations of “use” are found in the machine learning algorithms category. As time passed, the “use” motivations gradually replaced the “description” motivations for different algorithms, and the number of motivation types decreased significantly. Our research explores the identification, distribution, and evolution of authors’ motivations for mentioning algorithm entities, which could provide a basis for future algorithm relationship identification and influence evaluation using motivations.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101550"},"PeriodicalIF":3.7,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141291971","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}

引用次数: 0

An ESTs detection research based on paper entity mapping: Combining scientific text modeling and neural prophet 基于论文实体映射的 EST 检测研究：科学文本建模与神经先知的结合

IF 3.7 2区管理学

Journal of Informetrics Pub Date : 2024-06-08 DOI: 10.1016/j.joi.2024.101551

Dejian Yu, Bo Xiang

{"title":"An ESTs detection research based on paper entity mapping: Combining scientific text modeling and neural prophet","authors":"Dejian Yu, Bo Xiang","doi":"10.1016/j.joi.2024.101551","DOIUrl":"https://doi.org/10.1016/j.joi.2024.101551","url":null,"abstract":"<div><p>Existing studies on the detection of emerging scientific topics (ESTs) overemphasize the newness and neglect content innovation of knowledge. Moreover, they also ignore the lag existing in knowledge diffusion. In this paper, we propose a four-stage detection framework for ESTs that maps emerging attributes from paper entities to scientific topics. Empirical studies based on two significantly different disciplinary datasets, IS-LS, and AI, which contain 73,601 and 255,620 publications, respectively, are employed to validate our approach. First, we generate 29 and 47 candidate scientific topics based on topic modeling, respectively. Second, we represent the novelty of paper entities based on pre-trained language models, which is mapped to scientific topic entities along with knowledge distributions to obtain topic emerging attributes: topic novelty, relative share and growth. Third, we propose to predict future trends of these attributes with Neural Prophet, which outperforms four baseline models in <span><math><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup></math></span>, <span><math><mrow><mi>M</mi><mi>A</mi><mi>E</mi></mrow></math></span> and <span><math><mrow><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></math></span>. Finally, combining future values of candidate scientific topics, they are grouped into 8 clusters containing two ESTs types through strategic market theory and clustering model. From the correlation and feature distribution analysis of emerging attributes, we discover the existence of resilience and scale advantage in the diffusion of scientific knowledge. There also exists significant uncertainty in previous citation-based scientific topic evaluation patterns caused by the complexity of citation behavior. Overall, this research enriches theoretical knowledge and detection frameworks of ESTs, and provides detailed insights into comprehensive assessment and dissemination of scientific topics.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101551"},"PeriodicalIF":3.7,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141291912","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}

引用次数: 0