Yang Zhao, Mengting Zhang, Xiaoli Chen, Zhixiong Zhang
Purpose To address the “anomalies” that occur when scientific breakthroughs emerge, this study focuses on identifying early signs and nascent stages of breakthrough innovations from the perspective of outliers, aiming to achieve early identification of scientific breakthroughs in papers. Design/methodology/approach This study utilizes semantic technology to extract research entities from the titles and abstracts of papers to represent each paper’s research content. Outlier detection methods are then employed to measure and analyze the anomalies in breakthrough papers during their early stages. The development and evolution process are traced using literature time tags. Finally, a case study is conducted using the key publications of the 2021 Nobel Prize laureates in Physiology or Medicine. Findings Through manual analysis of all identified outlier papers, the effectiveness of the proposed method for early identifying potential scientific breakthroughs is verified. Research limitations The study’s applicability has only been empirically tested in the biomedical field. More data from various fields are needed to validate the robustness and generalizability of the method. Practical implications This study provides a valuable supplement to current methods for early identification of scientific breakthroughs, effectively supporting technological intelligence decision-making and services. Originality/Value The study introduces a novel approach to early identification of scientific breakthroughs by leveraging outlier analysis of research entities, offering a more sensitive, precise, and fine-grained alternative method compared to traditional citation-based evaluations, which enhances the ability to identify nascent breakthrough innovations.
{"title":"Early identification of scientific breakthroughs through outlier analysis based on research entities","authors":"Yang Zhao, Mengting Zhang, Xiaoli Chen, Zhixiong Zhang","doi":"10.2478/jdis-2024-0027","DOIUrl":"https://doi.org/10.2478/jdis-2024-0027","url":null,"abstract":"Purpose To address the “anomalies” that occur when scientific breakthroughs emerge, this study focuses on identifying early signs and nascent stages of breakthrough innovations from the perspective of outliers, aiming to achieve early identification of scientific breakthroughs in papers. Design/methodology/approach This study utilizes semantic technology to extract research entities from the titles and abstracts of papers to represent each paper’s research content. Outlier detection methods are then employed to measure and analyze the anomalies in breakthrough papers during their early stages. The development and evolution process are traced using literature time tags. Finally, a case study is conducted using the key publications of the 2021 Nobel Prize laureates in Physiology or Medicine. Findings Through manual analysis of all identified outlier papers, the effectiveness of the proposed method for early identifying potential scientific breakthroughs is verified. Research limitations The study’s applicability has only been empirically tested in the biomedical field. More data from various fields are needed to validate the robustness and generalizability of the method. Practical implications This study provides a valuable supplement to current methods for early identification of scientific breakthroughs, effectively supporting technological intelligence decision-making and services. Originality/Value The study introduces a novel approach to early identification of scientific breakthroughs by leveraging outlier analysis of research entities, offering a more sensitive, precise, and fine-grained alternative method compared to traditional citation-based evaluations, which enhances the ability to identify nascent breakthrough innovations.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"49 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142203538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This study focuses on understanding the collaboration relationships among mathematicians, particularly those esteemed as elites, to reveal the structures of their communities and evaluate their impact on the field of mathematics. Design/methodology/approach Two community detection algorithms, namely Greedy Modularity Maximization and Infomap, are utilized to examine collaboration patterns among mathematicians. We conduct a comparative analysis of mathematicians’ centrality, emphasizing the influence of award-winning individuals in connecting network roles such as Betweenness, Closeness, and Harmonic centrality. Additionally, we investigate the distribution of elite mathematicians across communities and their relationships within different mathematical sub-fields. Findings The study identifies the substantial influence exerted by award-winning mathematicians in connecting network roles. The elite distribution across the network is uneven, with a concentration within specific communities rather than being evenly dispersed. Secondly, the research identifies a positive correlation between distinct mathematical sub-fields and the communities, indicating collaborative tendencies among scientists engaged in related domains. Lastly, the study suggests that reduced research diversity within a community might lead to a higher concentration of elite scientists within that specific community. Research limitations The study’s limitations include its narrow focus on mathematicians, which may limit the applicability of the findings to broader scientific fields. Issues with manually collected data affect the reliability of conclusions about collaborative networks. Practical implications This study offers valuable insights into how elite mathematicians collaborate and how knowledge is disseminated within mathematical circles. Understanding these collaborative behaviors could aid in fostering better collaboration strategies among mathematicians and institutions, potentially enhancing scientific progress in mathematics. Originality/value The study adds value to understanding collaborative dynamics within the realm of mathematics, offering a unique angle for further exploration and research.
{"title":"Community detection on elite mathematicians’ collaboration network","authors":"Yurui Huang, Zimo Wang, Chaolin Tian, Yifang Ma","doi":"10.2478/jdis-2024-0026","DOIUrl":"https://doi.org/10.2478/jdis-2024-0026","url":null,"abstract":"Purpose This study focuses on understanding the collaboration relationships among mathematicians, particularly those esteemed as elites, to reveal the structures of their communities and evaluate their impact on the field of mathematics. Design/methodology/approach Two community detection algorithms, namely Greedy Modularity Maximization and Infomap, are utilized to examine collaboration patterns among mathematicians. We conduct a comparative analysis of mathematicians’ centrality, emphasizing the influence of award-winning individuals in connecting network roles such as Betweenness, Closeness, and Harmonic centrality. Additionally, we investigate the distribution of elite mathematicians across communities and their relationships within different mathematical sub-fields. Findings The study identifies the substantial influence exerted by award-winning mathematicians in connecting network roles. The elite distribution across the network is uneven, with a concentration within specific communities rather than being evenly dispersed. Secondly, the research identifies a positive correlation between distinct mathematical sub-fields and the communities, indicating collaborative tendencies among scientists engaged in related domains. Lastly, the study suggests that reduced research diversity within a community might lead to a higher concentration of elite scientists within that specific community. Research limitations The study’s limitations include its narrow focus on mathematicians, which may limit the applicability of the findings to broader scientific fields. Issues with manually collected data affect the reliability of conclusions about collaborative networks. Practical implications This study offers valuable insights into how elite mathematicians collaborate and how knowledge is disseminated within mathematical circles. Understanding these collaborative behaviors could aid in fostering better collaboration strategies among mathematicians and institutions, potentially enhancing scientific progress in mathematics. Originality/value The study adds value to understanding collaborative dynamics within the realm of mathematics, offering a unique angle for further exploration and research.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"4 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142203534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023. By integrating bibliometric analysis with expert insights from the Deeptime Digital Earth (DDE) initiative, this article identifies key emerging themes shaping the landscape of Earth Sciences①. Design/methodology/approach The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database. To map relationships between articles, citation networks were constructed, and spectral clustering algorithms were then employed to identify groups of related research, resulting in 407 clusters. Relevant research terms were extracted using the Log-Likelihood Ratio (LLR) algorithm, followed by statistical analyses on the volume of papers, average publication year, and average citation count within each cluster. Additionally, expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation, relevance, and impact within Geosciences, and finalize naming of these top trends with consideration of the content and implications of the associated research. This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists. Findings Thirty significant trends were identified in the field of Geosciences, spanning five domains: deep space, deep time, deep Earth, habitable Earth, and big data. These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society, science, and technology. Research limitations The analyzed data of this study only contain those were included in the Web of Science. Practical implications This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science, especially on solid earth. The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study. Originality/value This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting.
目的 本文深入分析了 2014 至 2023 年地球科学领域的全球研究趋势。通过将文献计量分析与 "Deeptime 数字地球"（DDE）计划的专家见解相结合，本文确定了影响地球科学前景的关键新兴主题①。设计/方法/途径 识别过程包括对来自 466 种地球科学期刊的 400,000 多篇论文和来自 93 种跨学科期刊的约 5,800 篇论文进行细致分析，这些论文均来自 Web of Science 和 Dimensions 数据库。为了绘制文章之间的关系图，我们构建了引文网络，然后采用频谱聚类算法来识别相关的研究群组，最终形成了 407 个群组。使用对数似然比（LLR）算法提取相关研究术语，然后对每个聚类中的论文数量、平均发表年份和平均引用次数进行统计分析。此外，还利用 DDE 科学委员会的专家知识，根据其在地球科学领域的代表性、相关性和影响力，选出了前 30 大趋势，并在考虑相关研究的内容和影响的基础上，最终确定了这些趋势的命名。这种全面的方法以地质科学家可以理解的方式系统地划分和描述了各种趋势。研究结果 确定了地球科学领域的 30 个重大趋势，涵盖五个领域：深空、深时、深地、宜居地球和大数据。这些主题反映了地球科学领域的最新趋势和进展，并有可能解决现实世界中与社会、科学和技术密切相关的问题。研究局限性 本研究的分析数据仅包含 Web of Science 中收录的数据。实际意义 本研究将有力地支持组织和科学家个人了解地球科学的现代前沿，特别是固体地球。调查机构或自然科学基金等组织可以参考本研究，规划未来探索的领域并分析热点话题。原创性/价值 本文将文献计量分析与专家见解相结合，突出了地球科学最重要的发展趋势，并通过全球投票的方式传达给科学家个人和公众。
{"title":"Data-enhanced revealing of trends in Geoscience","authors":"Yu Zhao, Meng Wang, Jiaxin Ding, Jiexing Qi, Lyuwen Wu, Sibo Zhang, Luoyi Fu, Xinbing Wang, Li Cheng","doi":"10.2478/jdis-2024-0023","DOIUrl":"https://doi.org/10.2478/jdis-2024-0023","url":null,"abstract":"Purpose This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023. By integrating bibliometric analysis with expert insights from the Deeptime Digital Earth (DDE) initiative, this article identifies key emerging themes shaping the landscape of Earth Sciences<jats:sup>①</jats:sup>. Design/methodology/approach The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database. To map relationships between articles, citation networks were constructed, and spectral clustering algorithms were then employed to identify groups of related research, resulting in 407 clusters. Relevant research terms were extracted using the Log-Likelihood Ratio (LLR) algorithm, followed by statistical analyses on the volume of papers, average publication year, and average citation count within each cluster. Additionally, expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation, relevance, and impact within Geosciences, and finalize naming of these top trends with consideration of the content and implications of the associated research. This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists. Findings Thirty significant trends were identified in the field of Geosciences, spanning five domains: deep space, deep time, deep Earth, habitable Earth, and big data. These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society, science, and technology. Research limitations The analyzed data of this study only contain those were included in the Web of Science. Practical implications This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science, especially on solid earth. The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study. Originality/value This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"80 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Interdisciplinary research plays a crucial role in addressing complex problems by integrating knowledge from multiple disciplines. This integration fosters innovative solutions and enhances understanding across various fields. This study explores the historical and sociological development of interdisciplinary research and maps its evolution through three distinct phases: pre-disciplinary, disciplinary, and post-disciplinary. It identifies key internal dynamics, such as disciplinary diversification, reorganization, and innovation, as primary drivers of this evolution. Additionally, this study highlights how external factors, particularly the urgency of World War II and the subsequent political and economic changes, have accelerated its advancement. The rise of interdisciplinary research has significantly reshaped traditional educational paradigms, promoting its integration across different educational levels. However, the inherent contradictions within interdisciplinary research present cognitive, emotional, and institutional challenges for researchers. Meanwhile, finding a balance between the breadth and depth of knowledge remains a critical challenge in interdisciplinary education.
{"title":"Navigating interdisciplinary research: Historical progression and contemporary challenges","authors":"Xiaoqiang Li, Fen Cai, Jintao Bao, Yuqing Jian, Zehui Sun, Xin Xie","doi":"10.2478/jdis-2024-0025","DOIUrl":"https://doi.org/10.2478/jdis-2024-0025","url":null,"abstract":"Interdisciplinary research plays a crucial role in addressing complex problems by integrating knowledge from multiple disciplines. This integration fosters innovative solutions and enhances understanding across various fields. This study explores the historical and sociological development of interdisciplinary research and maps its evolution through three distinct phases: pre-disciplinary, disciplinary, and post-disciplinary. It identifies key internal dynamics, such as disciplinary diversification, reorganization, and innovation, as primary drivers of this evolution. Additionally, this study highlights how external factors, particularly the urgency of World War II and the subsequent political and economic changes, have accelerated its advancement. The rise of interdisciplinary research has significantly reshaped traditional educational paradigms, promoting its integration across different educational levels. However, the inherent contradictions within interdisciplinary research present cognitive, emotional, and institutional challenges for researchers. Meanwhile, finding a balance between the breadth and depth of knowledge remains a critical challenge in interdisciplinary education.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"187 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ziyan Xu, Hongqi Han, Linna Li, Junsheng Zhang, Zexu Zhou
Purpose A text generation based multidisciplinary problem identification method is proposed, which does not rely on a large amount of data annotation. Design/methodology/approach The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique; second, it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model; third, it extracts problem phrases from generated titles according to regular expression rules; fourth, it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm; finally, it identifies multidisciplinary problems based on the disciplinary labels of papers. Findings Experiments in the “Carbon Peaking and Carbon Neutrality” field show that the proposed method can effectively identify multidisciplinary research problems. The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field. Research limitations It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness. Practical implications Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments, fund valuable multidisciplinary problems for research management authorities, and borrow ideas from other disciplines for researchers. Originality/value This approach proposes a novel multidisciplinary problem identification method based on text generation, which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques.
{"title":"Identifying multidisciplinary problems from scientific publications based on a text generation method","authors":"Ziyan Xu, Hongqi Han, Linna Li, Junsheng Zhang, Zexu Zhou","doi":"10.2478/jdis-2024-0021","DOIUrl":"https://doi.org/10.2478/jdis-2024-0021","url":null,"abstract":"Purpose A text generation based multidisciplinary problem identification method is proposed, which does not rely on a large amount of data annotation. Design/methodology/approach The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique; second, it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model; third, it extracts problem phrases from generated titles according to regular expression rules; fourth, it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm; finally, it identifies multidisciplinary problems based on the disciplinary labels of papers. Findings Experiments in the “Carbon Peaking and Carbon Neutrality” field show that the proposed method can effectively identify multidisciplinary research problems. The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field. Research limitations It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness. Practical implications Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments, fund valuable multidisciplinary problems for research management authorities, and borrow ideas from other disciplines for researchers. Originality/value This approach proposes a novel multidisciplinary problem identification method based on text generation, which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"39 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141777492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This study investigated the publication behaviour of 573 chief editors managing 432 Social Sciences journals in Turkey. Direct inquiries into editorial qualifications are rare, and this research aims to shed light on editors’ scientific leadership capabilities. Design/methodology/approach This study contrasts insider publication behaviour in national journals with international articles in journals indexed by the Web of Science (WOS) and Scopus. It argues that editors demonstrating a consistent ability to publish in competitive WOS and Scopus indexed journals signal high qualifications, while editors with persistent insider behaviour and strong local orientation signal low qualification. Scientific leadership capability is measured by first-authored publications. Correlation and various regression tests are conducted to identify significant determinants of publication behaviour. Findings International publications are rare and concentrated on a few individuals, while insider publications are endemic and constitute nearly 40% of all national articles. Editors publish 3.2 insider papers and 8.1 national papers for every SSCI article. 62% (58%) of the editors have no SSCI (Scopus) article, 53% (63%) do not have a single lead-authored WOS (Scopus) article, and 89% publish at least one insider paper. Only a minority consistently publish in international journals; a fifth of the editors have three or more SSCI publications, and a quarter have three or more Scopus articles. Editors with foreign Ph.D. degrees are the most qualified and internationally oriented, whereas non-mobile editors are the most underqualified and underperform other editors by every measure. Illustrating the overall lack of qualification, nearly half of the professor editors and the majority of the WOS and Scopus indexed journal editors have no record of SSCI or Scopus publications. Research limitations This research relies on local settings that encourage national publications at the expense of international journals. Findings should be evaluated in light of this setting and bearing in mind that narrow localities are more prone to peer favouritism. Practical implications Incompetent and nepotistic editors pose an imminent threat to Turkish national literature. A lasting solution would likely include the dismissal and replacement of unqualified editors, as well as delisting and closure of dozens of journals that operate in questionable ways and serve little scientific purpose. Originality/value To my knowledge, this is the first study to document the publication behaviour of national journal chief editors.
{"title":"Publication behaviour and (dis)qualification of chief editors in Turkish national Social Sciences journals","authors":"Lokman Tutuncu","doi":"10.2478/jdis-2024-0022","DOIUrl":"https://doi.org/10.2478/jdis-2024-0022","url":null,"abstract":"Purpose This study investigated the publication behaviour of 573 chief editors managing 432 Social Sciences journals in Turkey. Direct inquiries into editorial qualifications are rare, and this research aims to shed light on editors’ scientific leadership capabilities. Design/methodology/approach This study contrasts insider publication behaviour in national journals with international articles in journals indexed by the Web of Science (WOS) and Scopus. It argues that editors demonstrating a consistent ability to publish in competitive WOS and Scopus indexed journals signal high qualifications, while editors with persistent insider behaviour and strong local orientation signal low qualification. Scientific leadership capability is measured by first-authored publications. Correlation and various regression tests are conducted to identify significant determinants of publication behaviour. Findings International publications are rare and concentrated on a few individuals, while insider publications are endemic and constitute nearly 40% of all national articles. Editors publish 3.2 insider papers and 8.1 national papers for every SSCI article. 62% (58%) of the editors have no SSCI (Scopus) article, 53% (63%) do not have a single lead-authored WOS (Scopus) article, and 89% publish at least one insider paper. Only a minority consistently publish in international journals; a fifth of the editors have three or more SSCI publications, and a quarter have three or more Scopus articles. Editors with foreign Ph.D. degrees are the most qualified and internationally oriented, whereas non-mobile editors are the most underqualified and underperform other editors by every measure. Illustrating the overall lack of qualification, nearly half of the professor editors and the majority of the WOS and Scopus indexed journal editors have no record of SSCI or Scopus publications. Research limitations This research relies on local settings that encourage national publications at the expense of international journals. Findings should be evaluated in light of this setting and bearing in mind that narrow localities are more prone to peer favouritism. Practical implications Incompetent and nepotistic editors pose an imminent threat to Turkish national literature. A lasting solution would likely include the dismissal and replacement of unqualified editors, as well as delisting and closure of dozens of journals that operate in questionable ways and serve little scientific purpose. Originality/value To my knowledge, this is the first study to document the publication behaviour of national journal chief editors.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"45 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141777528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xintong Zhao, Kyle Langlois, Jacob Furst, Yuan An, Xiaohua Hu, Diego Gomez Gualdron, Fernando Uribe-Romo, Jane Greenberg
Purpose This paper reports on a scientometric analysis bolstered by human-in-the-loop, domain experts, to examine the field of metal-organic frameworks (MOFs) research. Scientometric analyses reveal the intellectual landscape of a field. The study engaged MOF scientists in the design and review of our research workflow. MOF materials are an essential component in next-generation renewable energy storage and biomedical technologies. The research approach demonstrates how engaging experts, via human-in-the-loop processes, can help develop a comprehensive view of a field’s research trends, influential works, and specialized topics. Design/methodology/approach A scientometric analysis was conducted, integrating natural language processing (NLP), topic modeling, and network analysis methods. The analytical approach was enhanced through a human-in-the-loop iterative process involving MOF research scientists at selected intervals. MOF researcher feedback was incorporated into our method. The data sample included 65,209 MOF research articles. Python3 and software tool VOSviewer were used to perform the analysis. Findings The findings demonstrate the value of including domain experts in research workflows, refinement, and interpretation of results. At each stage of the analysis, the MOF researchers contributed to interpreting the results and method refinements targeting our focus on MOF research. This study identified influential works and their themes. Our findings also underscore four main MOF research directions and applications. Research limitations This study is limited by the sample (articles identified and referenced by the Cambridge Structural Database) that informed our analysis. Practical implications Our findings contribute to addressing the current gap in fully mapping out the comprehensive landscape of MOF research. Additionally, the results will help domain scientists target future research directions. Originality/value To the best of our knowledge, the number of publications collected for analysis exceeds those of previous studies. This enabled us to explore a more extensive body of MOF research compared to previous studies. Another contribution of our work is the iterative engagement of domain scientists, who brought in-depth, expert interpretation to the data analysis, helping hone the study.
{"title":"Research evolution of metal organic frameworks: A scientometric approach with human-in-the-loop","authors":"Xintong Zhao, Kyle Langlois, Jacob Furst, Yuan An, Xiaohua Hu, Diego Gomez Gualdron, Fernando Uribe-Romo, Jane Greenberg","doi":"10.2478/jdis-2024-0019","DOIUrl":"https://doi.org/10.2478/jdis-2024-0019","url":null,"abstract":"Purpose This paper reports on a scientometric analysis bolstered by human-in-the-loop, domain experts, to examine the field of metal-organic frameworks (MOFs) research. Scientometric analyses reveal the intellectual landscape of a field. The study engaged MOF scientists in the design and review of our research workflow. MOF materials are an essential component in next-generation renewable energy storage and biomedical technologies. The research approach demonstrates how engaging experts, via human-in-the-loop processes, can help develop a comprehensive view of a field’s research trends, influential works, and specialized topics. Design/methodology/approach A scientometric analysis was conducted, integrating natural language processing (NLP), topic modeling, and network analysis methods. The analytical approach was enhanced through a human-in-the-loop iterative process involving MOF research scientists at selected intervals. MOF researcher feedback was incorporated into our method. The data sample included 65,209 MOF research articles. Python3 and software tool <jats:italic>VOSviewer</jats:italic> were used to perform the analysis. Findings The findings demonstrate the value of including domain experts in research workflows, refinement, and interpretation of results. At each stage of the analysis, the MOF researchers contributed to interpreting the results and method refinements targeting our focus on MOF research. This study identified influential works and their themes. Our findings also underscore four main MOF research directions and applications. Research limitations This study is limited by the sample (articles identified and referenced by the Cambridge Structural Database) that informed our analysis. Practical implications Our findings contribute to addressing the current gap in fully mapping out the comprehensive landscape of MOF research. Additionally, the results will help domain scientists target future research directions. Originality/value To the best of our knowledge, the number of publications collected for analysis exceeds those of previous studies. This enabled us to explore a more extensive body of MOF research compared to previous studies. Another contribution of our work is the iterative engagement of domain scientists, who brought in-depth, expert interpretation to the data analysis, helping hone the study.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"61 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers. This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network. Design/methodology/approach Key Nobel Prize-winning publications (NPs) in fields of gene engineering and astrophysics are regarded as a proxy for transformative research. In this contribution, we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact. Findings The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics. Research limitations The selection of Nobel Prizes is not balanced and the database used in this study, Dimensions, suffers from incompleteness and inaccuracy of citation links. Practical implications Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact. Originality/value This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.
{"title":"Tracking direct and indirect impact on technology and policy of transformative research via ego citation network","authors":"Xian Li, Xiaojun Hu","doi":"10.2478/jdis-2024-0018","DOIUrl":"https://doi.org/10.2478/jdis-2024-0018","url":null,"abstract":"Purpose The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers. This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network. Design/methodology/approach Key Nobel Prize-winning publications (NPs) in fields of gene engineering and astrophysics are regarded as a proxy for transformative research. In this contribution, we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact. Findings The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics. Research limitations The selection of Nobel Prizes is not balanced and the database used in this study, <jats:italic>Dimensions</jats:italic>, suffers from incompleteness and inaccuracy of citation links. Practical implications Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact. Originality/value This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"138 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Large Language Models (LLMs), exemplified by ChatGPT, have significantly reshaped text generation, particularly in the realm of writing assistance. While ethical considerations underscore the importance of transparently acknowledging LLM use, especially in scientific communication, genuine acknowledgment remains infrequent. A potential avenue to encourage accurate acknowledging of LLM-assisted writing involves employing automated detectors. Our evaluation of four cutting-edge LLM-generated text detectors reveals their suboptimal performance compared to a simple ad-hoc detector designed to identify abrupt writing style changes around the time of LLM proliferation. We contend that the development of specialized detectors exclusively dedicated to LLM-assisted writing detection is necessary. Such detectors could play a crucial role in fostering more authentic recognition of LLM involvement in scientific communication, addressing the current challenges in acknowledgment practices.
{"title":"Detecting LLM-assisted writing in scientific communication: Are we there yet?","authors":"Teddy Lazebnik, Ariel Rosenfeld","doi":"10.2478/jdis-2024-0020","DOIUrl":"https://doi.org/10.2478/jdis-2024-0020","url":null,"abstract":"Large Language Models (LLMs), exemplified by ChatGPT, have significantly reshaped text generation, particularly in the realm of writing assistance. While ethical considerations underscore the importance of transparently acknowledging LLM use, especially in scientific communication, genuine acknowledgment remains infrequent. A potential avenue to encourage accurate acknowledging of LLM-assisted writing involves employing automated detectors. Our evaluation of four cutting-edge LLM-generated text detectors reveals their suboptimal performance compared to a simple ad-hoc detector designed to identify abrupt writing style changes around the time of LLM proliferation. We contend that the development of specialized detectors exclusively dedicated to LLM-assisted writing detection is necessary. Such detectors could play a crucial role in fostering more authentic recognition of LLM involvement in scientific communication, addressing the current challenges in acknowledgment practices.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"26 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141577787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This study aims to evaluate the accuracy of authorship attributions in scientific publications, focusing on the fairness and precision of individual contributions within academic works. Design/methodology/approach The study analyzes 81,823 publications from the journal PLOS ONE, covering the period from January 2018 to June 2023. It examines the authorship attributions within these publications to try and determine the prevalence of inappropriate authorship. It also investigates the demographic and professional profiles of affected authors, exploring trends and potential factors contributing to inaccuracies in authorship. Findings Surprisingly, 9.14% of articles feature at least one author with inappropriate authorship, affecting over 14,000 individuals (2.56% of the sample). Inappropriate authorship is more concentrated in Asia, Africa, and specific European countries like Italy. Established researchers with significant publication records and those affiliated with companies or nonprofits show higher instances of potential monetary authorship. Research limitations Our findings are based on contributions as declared by the authors, which implies a degree of trust in their transparency. However, this reliance on self-reporting may introduce biases or inaccuracies into the dataset. Further research could employ additional verification methods to enhance the reliability of the findings. Practical implications These findings have significant implications for journal publishers, highlighting the necessity for robust control mechanisms to ensure the integrity of authorship attributions. Moreover, researchers must exercise discernment in determining when to acknowledge a contributor and when to include them in the author list. Addressing these issues is crucial for maintaining the credibility and fairness of academic publications. Originality/value This study contributes to an understanding of critical issues within academic authorship, shedding light on the prevalence and impact of inappropriate authorship attributions. By calling for a nuanced approach to ensure accurate credit is given where it is due, the study underscores the importance of upholding ethical standards in scholarly publishing.
{"title":"Beyond authorship: Analyzing contributions in PLOS ONE and the challenges of appropriate attribution","authors":"Abdelghani Maddi, Jaime A. Teixeira da Silva","doi":"10.2478/jdis-2024-0015","DOIUrl":"https://doi.org/10.2478/jdis-2024-0015","url":null,"abstract":"Purpose This study aims to evaluate the accuracy of authorship attributions in scientific publications, focusing on the fairness and precision of individual contributions within academic works. Design/methodology/approach The study analyzes 81,823 publications from the journal <jats:italic>PLOS ONE</jats:italic>, covering the period from January 2018 to June 2023. It examines the authorship attributions within these publications to try and determine the prevalence of inappropriate authorship. It also investigates the demographic and professional profiles of affected authors, exploring trends and potential factors contributing to inaccuracies in authorship. Findings Surprisingly, 9.14% of articles feature at least one author with inappropriate authorship, affecting over 14,000 individuals (2.56% of the sample). Inappropriate authorship is more concentrated in Asia, Africa, and specific European countries like Italy. Established researchers with significant publication records and those affiliated with companies or nonprofits show higher instances of potential monetary authorship. Research limitations Our findings are based on contributions as declared by the authors, which implies a degree of trust in their transparency. However, this reliance on self-reporting may introduce biases or inaccuracies into the dataset. Further research could employ additional verification methods to enhance the reliability of the findings. Practical implications These findings have significant implications for journal publishers, highlighting the necessity for robust control mechanisms to ensure the integrity of authorship attributions. Moreover, researchers must exercise discernment in determining when to acknowledge a contributor and when to include them in the author list. Addressing these issues is crucial for maintaining the credibility and fairness of academic publications. Originality/value This study contributes to an understanding of critical issues within academic authorship, shedding light on the prevalence and impact of inappropriate authorship attributions. By calling for a nuanced approach to ensure accurate credit is given where it is due, the study underscores the importance of upholding ethical standards in scholarly publishing.","PeriodicalId":44622,"journal":{"name":"Journal of Data and Information Science","volume":"75 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141187893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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