Pub Date : 2025-08-01DOI: 10.1016/j.joi.2025.101714
Giuseppe Giordano , Michelangelo Misuraca , Marialuisa Restaino
This research addresses the need to understand how quickly scientific papers gain citations. Survival analysis is employed to model the time until papers receive their first citation. Leveraging the Kaplan-Meier estimator and the discrete-time model, the study evaluates the likelihood of citation over time and analyses factors influencing citation speed, focusing on the number of coauthors, the journal's impact factor, and the number of cited references. The approach is applied to a set of top journals in the Information Science & Library Science subject category defined by Web of Science. The main findings reveal notable differences in the citation probability between different journals, with specific sources exhibiting faster citation rates. By modelling citation speed, the study offers a data-driven basis for informed journal selection, aimed at maximising early scholarly recognition. It provides a practical, empirically grounded decision-support framework for authors seeking timely scientific appraisal through strategic journal selection.
这项研究解决了理解科学论文获得引用的速度有多快的需求。生存分析用于模拟论文收到第一次引用之前的时间。利用Kaplan-Meier估计器和离散时间模型，该研究评估了随时间变化的被引可能性，并分析了影响被引速度的因素，重点关注合著者数量、期刊影响因子和被引参考文献数量。该方法应用于信息科学领域的一组顶级期刊。由Web of Science定义的图书馆学学科类别。主要研究结果显示，不同期刊之间的被引率存在显著差异，特定来源的被引率更高。通过对引用速度进行建模，该研究为知情期刊选择提供了数据驱动的基础，旨在最大限度地提高早期学术认可。它为作者通过战略性期刊选择寻求及时的科学评价提供了一个实用的、基于经验的决策支持框架。
{"title":"Evaluating the speed of citation in scientific journals: A survival analysis-based approach","authors":"Giuseppe Giordano , Michelangelo Misuraca , Marialuisa Restaino","doi":"10.1016/j.joi.2025.101714","DOIUrl":"10.1016/j.joi.2025.101714","url":null,"abstract":"<div><div>This research addresses the need to understand how quickly scientific papers gain citations. Survival analysis is employed to model the time until papers receive their first citation. Leveraging the Kaplan-Meier estimator and the discrete-time model, the study evaluates the likelihood of citation over time and analyses factors influencing citation speed, focusing on the number of coauthors, the journal's impact factor, and the number of cited references. The approach is applied to a set of top journals in the Information Science & Library Science subject category defined by Web of Science. The main findings reveal notable differences in the citation probability between different journals, with specific sources exhibiting faster citation rates. By modelling citation speed, the study offers a data-driven basis for informed journal selection, aimed at maximising early scholarly recognition. It provides a practical, empirically grounded decision-support framework for authors seeking timely scientific appraisal through strategic journal selection.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101714"},"PeriodicalIF":3.5,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810070","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}
Pub Date : 2025-07-30DOI: 10.1016/j.joi.2025.101709
Yanlan Kang , Chenwei Zhang , Zhuanlan Sun , Yiwei Li
The involvement of experienced peers as reviewers plays a crucial role in manuscript evaluation during the peer review process. Nonetheless, concerns have arisen regarding potential cognitive bias when reviewers assess research that is outside their areas of expertise. Despite these concerns, quantitative analysis of this issue remains limited. This study aims to empirically investigate whether submissions reviewed by peers with academic backgrounds similar to the authors’ research areas correlate with more rigorous comments during the peer review process. Utilizing a dataset of 2,147 papers published in the journal eLife, along with their publicly available peer review reports and reviewers’ publication records, we employed natural language processing techniques to measure the publication text similarity of reviewers to that of the manuscript’s authors, representing a minuscule part of intellectual proximity. We then used a linear regression model to examine whether such similarity was associated with review rigor, quantified by the frequency of statistical terms from two well-known glossaries. We observed no statistically significant differences in the rigor of comments made by peers with varying levels of publication text similarity in the constructed dataset and setting. The findings remained consistent across several robustness checks and alternative specifications. This suggests that no discernible cognitive bias is introduced by the reviewers’ academic background during the peer review process, enriching the extant literature and offering important insights into understanding the role of reviewers in maintaining fairness.
{"title":"Investigating the effect of publication text similarity between reviewers and authors on the rigor of peer review: An intellectual proximity perspective","authors":"Yanlan Kang , Chenwei Zhang , Zhuanlan Sun , Yiwei Li","doi":"10.1016/j.joi.2025.101709","DOIUrl":"10.1016/j.joi.2025.101709","url":null,"abstract":"<div><div>The involvement of experienced peers as reviewers plays a crucial role in manuscript evaluation during the peer review process. Nonetheless, concerns have arisen regarding potential cognitive bias when reviewers assess research that is outside their areas of expertise. Despite these concerns, quantitative analysis of this issue remains limited. This study aims to empirically investigate whether submissions reviewed by peers with academic backgrounds similar to the authors’ research areas correlate with more rigorous comments during the peer review process. Utilizing a dataset of 2,147 papers published in the journal <em>eLife</em>, along with their publicly available peer review reports and reviewers’ publication records, we employed natural language processing techniques to measure the publication text similarity of reviewers to that of the manuscript’s authors, representing a minuscule part of intellectual proximity. We then used a linear regression model to examine whether such similarity was associated with review rigor, quantified by the frequency of statistical terms from two well-known glossaries. We observed no statistically significant differences in the rigor of comments made by peers with varying levels of publication text similarity in the constructed dataset and setting. The findings remained consistent across several robustness checks and alternative specifications. This suggests that no discernible cognitive bias is introduced by the reviewers’ academic background during the peer review process, enriching the extant literature and offering important insights into understanding the role of reviewers in maintaining fairness.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101709"},"PeriodicalIF":3.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723707","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}
Pub Date : 2025-07-23DOI: 10.1016/j.joi.2025.101708
Youwei He, Jeong-Dong Lee
{"title":"Corrigendum to “Small but not least changes: The art of creating disruptive innovations” [Journal of Informetrics, Volume 19 , Issue 3, (August 2025), 101703]","authors":"Youwei He, Jeong-Dong Lee","doi":"10.1016/j.joi.2025.101708","DOIUrl":"10.1016/j.joi.2025.101708","url":null,"abstract":"","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101708"},"PeriodicalIF":3.4,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686811","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}
Pub Date : 2025-07-16DOI: 10.1016/j.joi.2025.101707
Dengsheng Wu , Qiudan Su , Jianping Li
Journal evaluation is essential for scientific research, influencing academic assessment, journal reputation, and the development of researchers. However, significant differences in journal quality evaluations across countries often contain ‘home bias’. To identify this bias, we propose an improved method based on the Oaxaca-Blinder decomposition, which has traditionally been used to analyse wage gaps and discrimination. Rather than relying on a hypothetical non-discrimination state that considers only the journal rankings of a single country, we employ the Weighted Average Percentile (WAP) approach to integrate journal rankings from multiple countries, thereby reflecting the evaluation consensus from a global perspective. This revision adapts the methodology to journal evaluation, offering a more comprehensive and balanced assessment of academic market expectations, and bringing it closer to an unbiased state in the journal evaluation process. Our analysis incorporated four national journal lists, comprising a total of 1,188 selected journals. We find that the Association of Business School (ABS) lists from the United Kingdom (UK) organizations exhibit 'home bias', favouring domestic journals and undervaluing foreign ones. This bias may impact the fairness of global scholarly communication and journal evaluation. Recognizing these home biases and transnational limitations is crucial when using journal lists.
{"title":"Identification of home bias in journal ranking lists","authors":"Dengsheng Wu , Qiudan Su , Jianping Li","doi":"10.1016/j.joi.2025.101707","DOIUrl":"10.1016/j.joi.2025.101707","url":null,"abstract":"<div><div>Journal evaluation is essential for scientific research, influencing academic assessment, journal reputation, and the development of researchers. However, significant differences in journal quality evaluations across countries often contain ‘home bias’. To identify this bias, we propose an improved method based on the Oaxaca-Blinder decomposition, which has traditionally been used to analyse wage gaps and discrimination. Rather than relying on a hypothetical non-discrimination state that considers only the journal rankings of a single country, we employ the Weighted Average Percentile (WAP) approach to integrate journal rankings from multiple countries, thereby reflecting the evaluation consensus from a global perspective. This revision adapts the methodology to journal evaluation, offering a more comprehensive and balanced assessment of academic market expectations, and bringing it closer to an unbiased state in the journal evaluation process. Our analysis incorporated four national journal lists, comprising a total of 1,188 selected journals. We find that the Association of Business School (ABS) lists from the United Kingdom (UK) organizations exhibit 'home bias', favouring domestic journals and undervaluing foreign ones. This bias may impact the fairness of global scholarly communication and journal evaluation. Recognizing these home biases and transnational limitations is crucial when using journal lists.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101707"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633443","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}
Pub Date : 2025-07-16DOI: 10.1016/j.joi.2025.101704
Gevorg Kesoyan , Ruzanna Shushanyan , Maria Ohanyan , Aleksan Shahkhatuni , Mariam Yeghikyan , Viktor Blaginin
After the Soviet Union's dissolution, Armenia faced a rigorous transition that profoundly affected its scientific infrastructure. The evolution of Armenia's scientific landscape following the collapse of the Soviet Union, has taken place during a period marked by significant challenges including reduced funding, a "brain drain," and a shift away from Soviet-era scientific priorities. In response, the Armenian government has implemented reforms to revitalize the scientific community, notably by establishing the State Science Committee in 2007 and introducing competitive research grant programs. The study analyzes the volume and trends of state research grants and their impact on scientific advancement in Armenia. The alignment of Armenian science with global standards and the visibility of scholarly output were assessed utilizing the Web of Science (WOS) database for quantitative analysis. Key objectives include evaluating the dynamics of research grants, identifying successful programs across academic fields, and exploring the implications for young scholars' career prospects. Findings reveal the transformative effects of these grants on both the quality and internationalization of Armenian research, providing insights into the role of state competitive funding in fostering a sustainable and innovative scientific environment.
{"title":"Boosting science through state support: Armenian state grants as a driver of scientific and international advancement","authors":"Gevorg Kesoyan , Ruzanna Shushanyan , Maria Ohanyan , Aleksan Shahkhatuni , Mariam Yeghikyan , Viktor Blaginin","doi":"10.1016/j.joi.2025.101704","DOIUrl":"10.1016/j.joi.2025.101704","url":null,"abstract":"<div><div>After the Soviet Union's dissolution, Armenia faced a rigorous transition that profoundly affected its scientific infrastructure. The evolution of Armenia's scientific landscape following the collapse of the Soviet Union, has taken place during a period marked by significant challenges including reduced funding, a \"brain drain,\" and a shift away from Soviet-era scientific priorities. In response, the Armenian government has implemented reforms to revitalize the scientific community, notably by establishing the State Science Committee in 2007 and introducing competitive research grant programs. The study analyzes the volume and trends of state research grants and their impact on scientific advancement in Armenia. The alignment of Armenian science with global standards and the visibility of scholarly output were assessed utilizing the Web of Science (WOS) database for quantitative analysis. Key objectives include evaluating the dynamics of research grants, identifying successful programs across academic fields, and exploring the implications for young scholars' career prospects. Findings reveal the transformative effects of these grants on both the quality and internationalization of Armenian research, providing insights into the role of state competitive funding in fostering a sustainable and innovative scientific environment.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101704"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144632823","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}
Scholarly communication is vital to scientific advancement, enabling the exchange of ideas and knowledge. When selecting publication venues, scholars consider various factors, such as journal relevance, reputation, outreach, and editorial standards and practices. However, some of these factors are inconspicuous or inconsistent across venues and individual publications. This study proposes that scholars' decision-making process can be conceptualized and explored through the biologically inspired exploration-exploitation (EE) framework, which posits that scholars balance between familiar and under-explored publication venues. Building on the EE framework, we introduce a grounded definition for “Home Venues” (HVs) – an informal concept used to describe the set of venues where a scholar consistently publishes – and investigate their emergence and key characteristics. Our analysis reveals that the publication patterns of roughly three-quarters of computer science scholars align with the expectations of the EE framework. For these scholars, HVs typically emerge and stabilize after approximately 15-20 publications. Additionally, scholars with higher h-indexes, greater number of publications, or higher academic age tend to have higher-ranking journals as their HVs.
{"title":"Publishing instincts: An exploration-exploitation framework for studying academic publishing behavior and “Home Venues”","authors":"Teddy Lazebnik , Shir Aviv-Reuven , Ariel Rosenfeld","doi":"10.1016/j.joi.2025.101705","DOIUrl":"10.1016/j.joi.2025.101705","url":null,"abstract":"<div><div>Scholarly communication is vital to scientific advancement, enabling the exchange of ideas and knowledge. When selecting publication venues, scholars consider various factors, such as journal relevance, reputation, outreach, and editorial standards and practices. However, some of these factors are inconspicuous or inconsistent across venues and individual publications. This study proposes that scholars' decision-making process can be conceptualized and explored through the biologically inspired exploration-exploitation (EE) framework, which posits that scholars balance between familiar and under-explored publication venues. Building on the EE framework, we introduce a grounded definition for “Home Venues” (HVs) – an informal concept used to describe the set of venues where a scholar consistently publishes – and investigate their emergence and key characteristics. Our analysis reveals that the publication patterns of roughly three-quarters of computer science scholars align with the expectations of the EE framework. For these scholars, HVs typically emerge and stabilize after approximately 15-20 publications. Additionally, scholars with higher h-indexes, greater number of publications, or higher academic age tend to have higher-ranking journals as their HVs.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101705"},"PeriodicalIF":3.4,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623710","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}
Pub Date : 2025-07-10DOI: 10.1016/j.joi.2025.101706
Zhenzhen Xu , Shengzhi Huang , Fan Zhang , Wei Lu , Yong Huang , Na Lu
The disruption index (DI) proposed by Funk and Owen-Smith (2017) is a practical metric that has been widely used to identify and analyze disruptive research. However, it suffers from several limitations, such as susceptibility to authors’ manipulation, a narrow focus on the local citation network, and unreasonable convergence characteristics. To address these shortcomings, we propose a novel overshadowing disruption index (∆DI), based on the DI, that captures the disruptive quality of a focal paper by examining its overshadowing impact on its successors. Using 359 highly cited, 443 moderately cited, and 40 Nobel Prize-winning physics papers as research objects, we analyze the evolutionary trajectories of ∆DI and demonstrate its rationality via the statistical methods and GPT-4. Specifically, ∆DI presents a decay trend converging to zero, indicating that the disruptive impact of a paper declines over time. By analyzing papers’ research content via GPT-4, we further explain the decay trend from the perspective of semantic analysis. Additionally, we comprehensively examine ∆DI’s statistics and unveil its correlation with common DI-based metrics. Finally, we systematically verify the effectiveness of ∆DI by scrutinizing the relationship between ∆DI and future scientific impact. Our results show that ∆DI exhibits better predictive power than DI and DI5, and the combination of ΔDI and DI performs the best in predicting scientific impact.
{"title":"Quantifying the disruptiveness of a paper by analyzing how it overshadows its successors","authors":"Zhenzhen Xu , Shengzhi Huang , Fan Zhang , Wei Lu , Yong Huang , Na Lu","doi":"10.1016/j.joi.2025.101706","DOIUrl":"10.1016/j.joi.2025.101706","url":null,"abstract":"<div><div>The disruption index (DI) proposed by Funk and Owen-Smith (2017) is a practical metric that has been widely used to identify and analyze disruptive research. However, it suffers from several limitations, such as susceptibility to authors’ manipulation, a narrow focus on the local citation network, and unreasonable convergence characteristics. To address these shortcomings, we propose a novel overshadowing disruption index (∆DI), based on the DI, that captures the disruptive quality of a focal paper by examining its overshadowing impact on its successors. Using 359 highly cited, 443 moderately cited, and 40 Nobel Prize-winning physics papers as research objects, we analyze the evolutionary trajectories of ∆DI and demonstrate its rationality via the statistical methods and GPT-4. Specifically, ∆DI presents a decay trend converging to zero, indicating that the disruptive impact of a paper declines over time. By analyzing papers’ research content via GPT-4, we further explain the decay trend from the perspective of semantic analysis. Additionally, we comprehensively examine ∆DI’s statistics and unveil its correlation with common DI-based metrics. Finally, we systematically verify the effectiveness of ∆DI by scrutinizing the relationship between ∆DI and future scientific impact. Our results show that ∆DI exhibits better predictive power than DI and DI<sub>5</sub>, and the combination of ΔDI and DI performs the best in predicting scientific impact.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101706"},"PeriodicalIF":3.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588766","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}
Pub Date : 2025-07-10DOI: 10.1016/j.joi.2025.101703
Youwei He , Jeong-Dong Lee
In the ever-evolving landscape of technology, product innovation arises through the replacement of outdated technologies with novel advancements or through technological recombination. This study employs a genetic framework to represent products, extracting chromosomal data to construct a comprehensive product influence network of automobiles using a phylogenetic approach. By introducing the “Product Disruption Index” —inspired by the D index—into the product similarity space, we measure a product’s disruptiveness. Our findings on the decline in disruptiveness of automotive products align with trends observed in previous studies on patents and publications, and the Product Disruption Index is further validated and its credibility reinforced through two compelling case studies. Our statistical analysis reveals that disruptive innovations often arise from minor yet pivotal modifications. Furthermore, inheriting superior technologies from predecessors and making slight adjustments to key technologies are more effective in enhancing a product’s disruptiveness than extensive technological changes. Indeed, small steps taken on the shoulders of giants can lead to significant breakthroughs in disruptive innovation.
{"title":"Small but not least changes: The art of creating disruptive innovations","authors":"Youwei He , Jeong-Dong Lee","doi":"10.1016/j.joi.2025.101703","DOIUrl":"10.1016/j.joi.2025.101703","url":null,"abstract":"<div><div>In the ever-evolving landscape of technology, product innovation arises through the replacement of outdated technologies with novel advancements or through technological recombination. This study employs a genetic framework to represent products, extracting chromosomal data to construct a comprehensive product influence network of automobiles using a phylogenetic approach. By introducing the “Product Disruption Index” —inspired by the D index—into the product similarity space, we measure a product’s disruptiveness. Our findings on the decline in disruptiveness of automotive products align with trends observed in previous studies on patents and publications, and the Product Disruption Index is further validated and its credibility reinforced through two compelling case studies. Our statistical analysis reveals that disruptive innovations often arise from minor yet pivotal modifications. Furthermore, inheriting superior technologies from predecessors and making slight adjustments to key technologies are more effective in enhancing a product’s disruptiveness than extensive technological changes. Indeed, small steps taken on the shoulders of giants can lead to significant breakthroughs in disruptive innovation.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101703"},"PeriodicalIF":3.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588767","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}
By integrating theories of collective memory and innovation diffusion, we construct a citation-based scientific innovation collective memory network and define four types of authors: Original authors, Adopters, Collaborators, and Converters. Additionally, we introduce two new quantitative metrics—the Adopter Conversion Rate (CRA) and Author Conversion Rate (CRC)—to assess the role of collaboration in the diffusion of scientific innovations. Using datasets from APS, Medline, and DBLP, we selected the top 100 most-cited papers published over 20 years ago as our research samples. Through a comprehensive analysis of citation patterns, scientific collaboration networks, and conversion rates, we uncover the pathways and mechanisms of knowledge diffusion in the scientific community. Our findings reveal that scientific research collaboration not only accelerates the diffusion of scientific innovations from their inception but also, as trust-based relationships develop and strengthen, facilitates efficient knowledge sharing and the growth of innovative activities. Furthermore, collaboration facilitates the transition from communicative memory to cultural memory, ensuring the long-term preservation and transmission of scientific knowledge.
{"title":"From communicative to cultural memory: The role of collaboration in the diffusion of scientific innovation","authors":"Yujia Zhai , Ruolan Zhuang , Yue Liu , Jinwen Zhang , Ying Ding","doi":"10.1016/j.joi.2025.101699","DOIUrl":"10.1016/j.joi.2025.101699","url":null,"abstract":"<div><div>By integrating theories of collective memory and innovation diffusion, we construct a citation-based scientific innovation collective memory network and define four types of authors: Original authors, Adopters, Collaborators, and Converters. Additionally, we introduce two new quantitative metrics—the Adopter Conversion Rate (CRA) and Author Conversion Rate (CRC)—to assess the role of collaboration in the diffusion of scientific innovations. Using datasets from APS, Medline, and DBLP, we selected the top 100 most-cited papers published over 20 years ago as our research samples. Through a comprehensive analysis of citation patterns, scientific collaboration networks, and conversion rates, we uncover the pathways and mechanisms of knowledge diffusion in the scientific community. Our findings reveal that scientific research collaboration not only accelerates the diffusion of scientific innovations from their inception but also, as trust-based relationships develop and strengthen, facilitates efficient knowledge sharing and the growth of innovative activities. Furthermore, collaboration facilitates the transition from communicative memory to cultural memory, ensuring the long-term preservation and transmission of scientific knowledge.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101699"},"PeriodicalIF":3.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549776","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}
Pub Date : 2025-06-27DOI: 10.1016/j.joi.2025.101700
Wenceslao Arroyo-Machado , Nicolas Robinson-Garcia , Daniel Torres-Salinas
This study examines the shift in the scientific community from X (formerly Twitter) to Bluesky, its impact on scientific communication, and consequently on social metrics (altmetrics). We analysed 14,497 publications from multidisciplinary and Library and Information Science (LIS) journals between January 2024 and March 2025. The results reveal a notable increase in Bluesky activity for multidisciplinary journals in November 2024, likely influenced by political and platform changes, with mentions multiplying for journals like Nature and Science. In LIS, the adoption of Bluesky is different and shows marked variation between European and United States journals. Although Bluesky remains a minority platform compared to X over the whole period, when focusing on user engagement after the United States elections, we see a much more even distribution between the two platforms. In two LIS journals, Bluesky even surpasses X, while in most others, the difference in user engagement was no longer as pronounced, marking a significant change from previous patterns in altmetrics.
{"title":"Are there stars in Bluesky? A comparative exploratory analysis of altmetric mentions between X and Bluesky","authors":"Wenceslao Arroyo-Machado , Nicolas Robinson-Garcia , Daniel Torres-Salinas","doi":"10.1016/j.joi.2025.101700","DOIUrl":"10.1016/j.joi.2025.101700","url":null,"abstract":"<div><div>This study examines the shift in the scientific community from X (formerly Twitter) to Bluesky, its impact on scientific communication, and consequently on social metrics (altmetrics). We analysed 14,497 publications from multidisciplinary and Library and Information Science (LIS) journals between January 2024 and March 2025. The results reveal a notable increase in Bluesky activity for multidisciplinary journals in November 2024, likely influenced by political and platform changes, with mentions multiplying for journals like Nature and Science. In LIS, the adoption of Bluesky is different and shows marked variation between European and United States journals. Although Bluesky remains a minority platform compared to X over the whole period, when focusing on user engagement after the United States elections, we see a much more even distribution between the two platforms. In two LIS journals, Bluesky even surpasses X, while in most others, the difference in user engagement was no longer as pronounced, marking a significant change from previous patterns in altmetrics.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101700"},"PeriodicalIF":3.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490417","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}
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