Journal of Informetrics最新文献_第4页

An empirical study of retractions due to honest errors: Exploring the relationship between error types and author teams 对因诚实错误而撤稿的实证研究：探索错误类型与作者团队之间的关系

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-11-16 DOI: 10.1016/j.joi.2024.101600

Dong Wang , Sihan Chen

{"title":"An empirical study of retractions due to honest errors: Exploring the relationship between error types and author teams","authors":"Dong Wang , Sihan Chen","doi":"10.1016/j.joi.2024.101600","DOIUrl":"10.1016/j.joi.2024.101600","url":null,"abstract":"<div><div>By adopting binary logistic regression and using a dataset of retractions due to honest errors, this paper analyses the relationships between types of honest errors and the characteristics of author teams, aiming to make recommendations about research management for researchers and policy makers. The results show that (1) honest errors made by medium-sized teams are more likely to be data errors rather than other types of errors, than those made by other-sized teams; (2) overall, there is no obvious relationship between types of honest errors and collaboration patterns; (3) there is no significant difference in the probability that honest errors are data errors rather than other types of errors (called “the probability”), with or without the participation of US authors. Honest errors made by teams with the participation of Chinese authors are less likely to be data errors, than those made by teams without Chinese authors; (4) collaboration patterns moderate the relationship between types of honest errors and the participation of Chinese authors. Specifically, the probability is significantly greater for single-authored publications in China than in other countries, and the probability for domestic collaboration in China is much lower than that outside China. There is no significant difference in the probability for international collaboration publications in China and those in other countries.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 1","pages":"Article 101600"},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662202","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

Citation recommendation based on argumentative zoning of user queries 基于用户查询的论证分区的引文推荐

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-11-16 DOI: 10.1016/j.joi.2024.101607

Shutian Ma , Chengzhi Zhang , Heng Zhang , Zheng Gao

引用次数: 0

Metrics fraud on ResearchGate 研究门上的度量欺诈

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-11-16 DOI: 10.1016/j.joi.2024.101604

Savina Kirilova , Fred Zoepfl

引用次数: 0

How does Nobel prize awarding shift the research topics of Nobelists’ coauthors and non-coauthors? 诺贝尔奖是如何改变诺贝尔奖获得者的合作作者和非合作作者的研究课题的？

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-11-15 DOI: 10.1016/j.joi.2024.101602

Xin Xie , Jin Mao , Jiang Li

{"title":"How does Nobel prize awarding shift the research topics of Nobelists’ coauthors and non-coauthors?","authors":"Xin Xie , Jin Mao , Jiang Li","doi":"10.1016/j.joi.2024.101602","DOIUrl":"10.1016/j.joi.2024.101602","url":null,"abstract":"<div><div>In this study, we investigate the influence of the Nobel prize promulgation on the research attention of Nobelists’ coauthors, especially those who have closely collaborated with the laureates on the prizewinning topics before the promulgation. Do these coauthors follow the prevailing trend triggered by the Nobel prize and consequently increase their studies on the award topics? Or, conversely, do these coauthors curtail their research attention on the honored topics and divert their efforts to new research horizons? To scrutinize this question, we utilize the APS dataset and the publication records of Nobelists to discern coauthorships among scholars. Then we employ network construction and community detection methods to identify scholars' research topics throughout their careers. Besides, we utilized the Propensity Score Matching to construct a parallel sample of Nobelists’ non-coauthors, who had never coauthored a paper with the corresponding laureate but had published at least one paper on the prizewinning topic. Following this, our main result substantiates that, after the Nobel awarding, coauthors exhibit a discernible reduction in publications on the award topics than non-coauthors. And the distinct choices of research strategy among distinct groups of scholars may be explained by the potential information asymmetry and different understandings concerning the award topics, as well as their distinct research intuitions in determining research direction. This study not only contributes to enriching our comprehension of how scientific prizes play a role in shaping research strategies of scientists within the award filed, but also stands as one of the pioneering contributions that focus on Nobelists’ coauthors.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 1","pages":"Article 101602"},"PeriodicalIF":3.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662200","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

Deep learning meets bibliometrics: A survey of citation function classification 深度学习与文献计量学的结合：引文函数分类调查

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-11-14 DOI: 10.1016/j.joi.2024.101608

Yang Zhang , Yufei Wang , Quan Z. Sheng , Lina Yao , Haihua Chen , Kai Wang , Adnan Mahmood , Wei Emma Zhang , Munazza Zaib , Subhash Sagar , Rongying Zhao

{"title":"Deep learning meets bibliometrics: A survey of citation function classification","authors":"Yang Zhang , Yufei Wang , Quan Z. Sheng , Lina Yao , Haihua Chen , Kai Wang , Adnan Mahmood , Wei Emma Zhang , Munazza Zaib , Subhash Sagar , Rongying Zhao","doi":"10.1016/j.joi.2024.101608","DOIUrl":"10.1016/j.joi.2024.101608","url":null,"abstract":"<div><div>With the advent and progression of Natural Language Processing (NLP) methodologies, the domain of automatic citation function classification has gained popularity and considerable research efforts have been contributed to this task. Automatic citation function classification has a joint computational linguistic and bibliometrics background. However, due to the different expertise in both fields, there is rarely a comprehensive and unified analysis of this task. We provide a detailed and nuanced examination analysis of the evolution of citation function classification task from the dimensions of citation function annotation schemes, widely employed benchmarks, and computational models. We first present the origins and the development of the citation function classification task. From the perspective of multi-disciplinary integration, we then discuss how bibliometrics and NLP can be better combined to contribute to the citation function classification task. Finally, based on the deficiencies that we have found in the task, we suggest some promising prospects in both bibliometrics and NLP to be investigated.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 1","pages":"Article 101608"},"PeriodicalIF":3.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662203","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

Corrigendum to “Societal and scientific impact of policy research: A large-scale empirical study of some explanatory factors using Altmetric and Overton” [Journal of Informetrics 18/3 (2024) 101530] 政策研究的社会和科学影响：利用 Altmetric 和 Overton 对一些解释性因素的大规模实证研究》[《信息计量学杂志》18/3 (2024) 101530] 更正

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-11-01 DOI: 10.1016/j.joi.2024.101598

Pablo Dorta-González , Alejandro Rodríguez-Caro , María Isabel Dorta-González

引用次数: 0

Corrigendum to “Conscientiousness predicts doctoral students’ research productivity” [Journal of Informetrics 17/1 (2023) 101353] 对 "认真程度预测博士生的研究生产率 "的更正[《信息学杂志》17/1 (2023) 101353]

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-11-01 DOI: 10.1016/j.joi.2024.101599

Jonas Lindahl

引用次数: 0

Should we circumvent knowledge path dependency? The impact of conventional learning and collaboration diversity on knowledge creation 我们应该规避知识路径依赖吗？传统学习和协作多样性对知识创造的影响

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-10-19 DOI: 10.1016/j.joi.2024.101597

Le Chang , Huiying Zhang , Chao Zhang

{"title":"Should we circumvent knowledge path dependency? The impact of conventional learning and collaboration diversity on knowledge creation","authors":"Le Chang , Huiying Zhang , Chao Zhang","doi":"10.1016/j.joi.2024.101597","DOIUrl":"10.1016/j.joi.2024.101597","url":null,"abstract":"<div><div>The choice of research strategy is patterned by the essential tension between tradition and innovation. Drawing on the leadership continuum theory, this paper proposes a theoretical framework discussing the continuum of research strategy referred to as conventional learning. We explore how knowledge creation is affected by conventional learning and collaboration diversity. Relevant hypotheses are tested using data from the Web of Science (WoS) database between 1988 and 2018. The results indicate both focused and expansive conventional learning have a positive relationship with knowledge productivity, while they have a U-shaped effect on knowledge creativity. Collaboration diversity positively moderates the relationship between focused and expansive conventional learning and knowledge productivity. Furthermore, although low-level collaboration diversity is optimal for knowledge creativity when the level of conventional learning is low, high-level collaboration diversity is more beneficial for knowledge creativity when the level of conventional learning is high, both for focused and expansive. Our study provides important implications for creative individuals.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101597"},"PeriodicalIF":3.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535415","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

Predicting the emergence of disruptive technologies by comparing with references via soft prompt-aware shared BERT 通过软提示感知共享 BERT 与参考资料进行比较，预测颠覆性技术的出现

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-10-16 DOI: 10.1016/j.joi.2024.101596

Guoxiu He , Chenxi Lin , Jiayu Ren , Peichen Duan

{"title":"Predicting the emergence of disruptive technologies by comparing with references via soft prompt-aware shared BERT","authors":"Guoxiu He , Chenxi Lin , Jiayu Ren , Peichen Duan","doi":"10.1016/j.joi.2024.101596","DOIUrl":"10.1016/j.joi.2024.101596","url":null,"abstract":"<div><div>The exponential increase in the annual volume of publications places a significant challenge in assessing the disruptive potential of technologies in new papers. Prior approaches to identifying disruptive technologies based on the accumulation of paper citations are characterized by their limited prospective and time-consuming nature. Moreover, the total citation count fails to capture the intricate network of citations associated with the focal papers. Consequently, we advocate for the utilization of the disruption index instead of depending on citation counts. Particularly, we devise a novel neural network, called Soft Prompt-aware Shared BERT (<strong>SPS-BERT</strong>), to predict the potential technological disruption index of immediately published papers. It incorporates separate soft prompts to enable BERT examining comparative details within a paper's abstract and its references. Additionally, a tailored attention mechanism is employed to intensify the semantic comparison. Based on the enhanced representation derived from BERT, we utilize a linear layer to estimate potential disruption index. Experimental results demonstrate that SPS-BERT outperforms existing state-of-the-art methods in predicting five-year disruption index across the DBLP and PubMed datasets. Additionally, we conduct an evaluation of our model to predict the ten-year disruption index and five-year citation increments, demonstrating its robustness and scalability. Notably, our model's predictions of disruptive technologies, based on papers published in 2022, align with the expert assessments released by MIT, highlighting its practical significance. The code is available at <span><span>https://github.com/ECNU-Text-Computing/SPS-BERT</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101596"},"PeriodicalIF":3.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442191","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

Top research performance in Poland over three decades: A multidimensional micro-data approach 三十年来波兰的顶尖研究业绩：多维微观数据方法

IF 3.4 2区管理学

Journal of Informetrics Pub Date : 2024-10-03 DOI: 10.1016/j.joi.2024.101595

Marek Kwiek , Wojciech Roszka

{"title":"Top research performance in Poland over three decades: A multidimensional micro-data approach","authors":"Marek Kwiek , Wojciech Roszka","doi":"10.1016/j.joi.2024.101595","DOIUrl":"10.1016/j.joi.2024.101595","url":null,"abstract":"<div><div>In this research, the contributions of a highly productive minority of scientists to the national Polish research output over the past three decades (1992–2021) is explored. A large population of all internationally visible Polish scientists (<em>N</em> = 152,043) with their 587,558 articles is studied. In almost all previous research, the approaches to high research productivity are missing the time component. Cross-sectional studies were not complemented by longitudinal studies: Scientists comprising the classes of top performers have not been tracked over time. Three classes of top performers (the upper 1 %, 5 %, and 10 %) are examined, and a surprising temporal stability of productivity patterns is found. The 1/10 and 10/50 rules consistently apply across the three decades: The upper 1 % of scientists, on average, account for 10 % of the national output, and the upper 10 % account for almost 50 % of total output, with significant disciplinary variations. The Relative Presence Index (RPI) we constructed shows that men are overrepresented and women underrepresented in all top performers classes. Top performers are studied longitudinally through their detailed publishing histories, with micro-data coming from the raw Scopus dataset. Econometric models identify the three most important predictors that change the odds ratio estimates of membership in the top performance classes: gender, academic age, and research collaboration. The downward trend in fixed effects over successive six-year periods indicates increasing competition in Polish academia.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101595"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421894","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