{"title":"Conclusions need to follow from supporting results","authors":"Robin Haunschild , Lutz Bornmann","doi":"10.1016/j.joi.2024.101610","DOIUrl":"10.1016/j.joi.2024.101610","url":null,"abstract":"","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 1","pages":"Article 101610"},"PeriodicalIF":3.4,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701259","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}
Alexander Michael Petersen , Felber J. Arroyave , Fabio Pammolli
{"title":"The disruption index suffers from citation inflation: Re-analysis of temporal CD trend and relationship with team size reveal discrepancies","authors":"Alexander Michael Petersen , Felber J. Arroyave , Fabio Pammolli","doi":"10.1016/j.joi.2024.101605","DOIUrl":"10.1016/j.joi.2024.101605","url":null,"abstract":"<div><div>Measuring the rate of innovation in academia and industry is fundamental to monitoring the efficiency and competitiveness of the knowledge economy. To this end, a disruption index (CD) was recently developed and applied to publication and patent citation networks (<span><span>Wu et al., 2019</span></span>; <span><span>Park et al., 2023</span></span>). Here we show that CD systematically decreases over time due to secular growth in research production, following two distinct mechanisms unrelated to innovation – one behavioral and the other structural. Whereas the behavioral explanation reflects shifts associated with techno-social factors (e.g. self-citation practices), the structural explanation follows from ‘citation inflation’ (CI), an inextricable feature of real citation networks attributable to increasing reference list lengths, which causes CD to systematically decrease. We demonstrate this causal link by way of mathematical deduction, computational simulation, multi-variate regression, and quasi-experimental comparison of the disruptiveness of PNAS versus PNAS Plus articles, which differ primarily in their lengths. Accordingly, we analyze CD data available in the SciSciNet database and find that disruptiveness incrementally increased from 2005-2015, and that the negative relationship between disruption and team-size is remarkably small in overall magnitude effect size, and shifts from negative to positive for team size ≥ 8 coauthors.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 1","pages":"Article 101605"},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662281","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":"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}
{"title":"Citation recommendation based on argumentative zoning of user queries","authors":"Shutian Ma , Chengzhi Zhang , Heng Zhang , Zheng Gao","doi":"10.1016/j.joi.2024.101607","DOIUrl":"10.1016/j.joi.2024.101607","url":null,"abstract":"<div><div>Citation recommendation aims to locate the important papers for scholars to cite. When writing the citing sentences, the authors usually hold different citing intents, which are referred to citation function in citation analysis. Since argumentative zoning is to identify the argumentative and rhetorical structure in scientific literature, we want to use this information to improve the citation recommendation task. In this paper, a multi-task learning model is built for citation recommendation and argumentative zoning classification. We also generated an annotated corpus of the data from PubMed Central based on a new argumentative zoning schema. The experimental results show that, by considering the argumentative information in the citing sentence, citation recommendation model will get better performance.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 1","pages":"Article 101607"},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662201","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":"Metrics fraud on ResearchGate","authors":"Savina Kirilova , Fred Zoepfl","doi":"10.1016/j.joi.2024.101604","DOIUrl":"10.1016/j.joi.2024.101604","url":null,"abstract":"<div><div>The academic social networking site ResearchGate (RG) allows members to post refereed papers and non-refereed preprints on the service. RG provides service-specific metrics and altmetrics for authors and publications posted on the service such as Reads, Citations, Recommendations, h-index, and RI Scores. This paper identifies problems based on a review of examples of questionable practices, which raises concerns about the lack of transparency and the validity of RG's metrics and altmetrics to assess scientific reputation. The paper describes a scheme that small groups of researchers use to deliberately inflate each other's metrics on RG. Additionally, a comparison is made between an unethical physics researcher's RG metrics and those of several Physics Nobel Laureates. Based on the problems found, the paper proposes several corrective actions RG could implement to mitigate metrics fraud on the service.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 1","pages":"Article 101604"},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662282","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 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}
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}
Pablo Dorta-González , Alejandro Rodríguez-Caro , María Isabel Dorta-González
{"title":"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]","authors":"Pablo Dorta-González , Alejandro Rodríguez-Caro , María Isabel Dorta-González","doi":"10.1016/j.joi.2024.101598","DOIUrl":"10.1016/j.joi.2024.101598","url":null,"abstract":"","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101598"},"PeriodicalIF":3.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697345","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":"Corrigendum to “Conscientiousness predicts doctoral students’ research productivity” [Journal of Informetrics 17/1 (2023) 101353]","authors":"Jonas Lindahl","doi":"10.1016/j.joi.2024.101599","DOIUrl":"10.1016/j.joi.2024.101599","url":null,"abstract":"","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101599"},"PeriodicalIF":3.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697435","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":"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}