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学者姓名：刘俊婉
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Abstract ：
Within close scientific collaborations, partners trust and support each other. Super-partnerships emerge among scholars who are interconnected within tightly knit collaborative networks. Understanding the characteristics of super-partnerships is crucial for comprehending patterns of super-relationships and partner selection. In this paper, we introduce a new concept that defines a collaborative partner with a super tie as a "career partner". This study focuses on career partnerships within the field of economics, employing a relationship-centered Exponential Random Graph Model (ERGM) to identify the characteristics of career partners. A total of 3724 pairs of career partners were identified in economics. Several noteworthy findings regarding the characteristics of career partnerships are summarized as follows: (1) in terms of research level, career partners exhibit higher research productivity and longer careers, and scholars with a "similar standing" are more likely to become career partners than those with a "disparity in status"; (2) in terms of gender, "same-gender attraction" is more likely to foster strong relationships than "opposite-gender attraction"; (3) in terms of research topics, academics are more inclined to form super-connections with career partners who share "like-mindedness"; (4) in terms of geographical proximity, scholars who are "inseparable as body and shadow" are more likely to become career partners than those who are "far apart". Our findings suggest that academics are more likely to form career partnerships with partners who share similar characteristics. This paper explores the attributes of career partners and provides a new reference for researchers in selecting academic partners.
Keyword ：
Exponential random graph model Exponential random graph model Career partner Career partner Research collaboration Research collaboration
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| GB/T 7714 | Liu, Junwan , Cui, Zining , Huang, Chenchen et al. Choosing a career partner: birds of a feather flock together [J]. | SCIENTOMETRICS , 2025 . |
| MLA | Liu, Junwan et al. "Choosing a career partner: birds of a feather flock together" . | SCIENTOMETRICS (2025) . |
| APA | Liu, Junwan , Cui, Zining , Huang, Chenchen , Song, Yinglu . Choosing a career partner: birds of a feather flock together . | SCIENTOMETRICS , 2025 . |
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Abstract ：
Interdisciplinary research teams are crucial in solving complex problems by providing creative solutions that single-discipline teams cannot achieve. Despite considerable research has been conducted to enhance the efficacy of interdisciplinary teams, there is still a lack of understanding regarding the correlation between team diversity and innovative performance. Therefore, this study investigates this question thoroughly with the most influential scholars and their collaborators in artificial intelligence. Furthermore, decision tree algorithms were utilized to examine which interdisciplinary teams (according to diversity characteristics) are more likely to achieve high innovation performance, measured by novelty and impact. The results of the study show a U-shaped relationship between a combination of research interests diversity and member diversity and the "novelty" innovation performance. Specifically, teams exhibiting high diversity in research interests tend to demonstrate superior innovative performance, irrespective of member diversity. Conversely, teams with low research interest diversity can only attain higher novelty in their innovative performance if member diversity surpasses a certain threshold; otherwise, their novelty performance diminishes. Regarding "impact" innovation performance, teams characterized by higher member diversity, while maintaining research interest diversity within a reasonable range, are likely to achieve higher impact. Additionally, interdisciplinary teams that exhibit lower member diversity but higher institutional diversity also demonstrate enhanced performance. Moreover, the study found that research interest diversity served as the variable most strongly associated with team innovation performance. This study extends the research on the complex non-linear relationship between multi-factor combinations of team diversity and the innovative performance of interdisciplinary research teams.
Keyword ：
Interdisciplinary research team Interdisciplinary research team Classification and regression tree (CART) model Classification and regression tree (CART) model Team diversity Team diversity Innovation performance Innovation performance
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| GB/T 7714 | Liu, Junwan , Gong, Xiaoyun , Xu, Shuo et al. Understanding the relationship between team diversity and the innovative performance in research teams using decision tree algorithms: evidence from artificial intelligence [J]. | SCIENTOMETRICS , 2024 , 129 (12) : 7805-7831 . |
| MLA | Liu, Junwan et al. "Understanding the relationship between team diversity and the innovative performance in research teams using decision tree algorithms: evidence from artificial intelligence" . | SCIENTOMETRICS 129 . 12 (2024) : 7805-7831 . |
| APA | Liu, Junwan , Gong, Xiaoyun , Xu, Shuo , Huang, Chenchen . Understanding the relationship between team diversity and the innovative performance in research teams using decision tree algorithms: evidence from artificial intelligence . | SCIENTOMETRICS , 2024 , 129 (12) , 7805-7831 . |
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Abstract ：
In order to analyse the gender disparities in scientific research output in the field of economics, this paper selected the Web of Science database as the source database. We collected and screened 257,642 articles written by 130,397 authors from 1933 to 2017 in the field of economics. In this study, we use mathematical statistics and bibliometrics indexes to quantitatively analyse the gap between male and female authors in many aspects, including the output and influence in different level of journals and institutions, the dynamic evolution of output and influence and collaboration modes with gender disparities. In addition, we have analyzed the disparities in output and influence of male and female authors among different countries. The results show that male authors dominate in the economics research field according to their high output and influence. However, female authors also show advantage when it comes to the research influence. Finally, we conducted a dynamic analysis of the contribution and collaboration of men and women over the course of their careers, and our findings again demonstrate the importance of women's participation in scientific collaboration. This study can provide an insight of gender different in economics research.
Keyword ：
Economics Economics Gender disparities Gender disparities Contribution degree Contribution degree Output Output
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| GB/T 7714 | Liu, Junwan , Song, Yinglu , Yang, Sai . Gender disparities in the field of economics [J]. | SCIENTOMETRICS , 2020 , 125 (2) : 1477-1498 . |
| MLA | Liu, Junwan et al. "Gender disparities in the field of economics" . | SCIENTOMETRICS 125 . 2 (2020) : 1477-1498 . |
| APA | Liu, Junwan , Song, Yinglu , Yang, Sai . Gender disparities in the field of economics . | SCIENTOMETRICS , 2020 , 125 (2) , 1477-1498 . |
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Abstract ：
This paper introduces a novel quantitative metric called the Symbiosis Degree Index for measuring the degree of symbiosis between subjects, which we apply it to analyzing scientific collaboration patterns between researchers. We study the network characteristics of scientific collaboration based on the resultant published research papers indexed in the Web of Science, considering the role of symbiosis. Analyses through our symbiosis metric of the relationship between a pair of mentor and mentee show substantively distinct ramifications from the "old leads young" model. In a sustained collaboration relationship, young researchers do indeed draw support from mentors' resources to improve their own level of scientific productivity and influence (as predicted in earlier models), but mentors also benefit by increasing their own productivity in publications. The collaborative symbiosis degree between mentor and mentee changes over time as the relationship matures. In the particular case studied here, even though the mentor's output decreased later in the relationship, their influence (measured through citations) continued to develop at the same pace through these collaborations. This is intended to demonstrate the potential of the metric to produce new insights on the nature of collaboration.
Keyword ：
Collaborative productivity Collaborative productivity Collaborative influence Collaborative influence Mentor-mentee relationship Mentor-mentee relationship Research collaboration Research collaboration Symbiosis Degree Index Symbiosis Degree Index Scientific collaboration network Scientific collaboration network
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| GB/T 7714 | Liu, Junwan , Ding, Kaiyue , Wang, Feifei et al. The structure and evolution of scientific collaboration from the perspective of symbiosis [J]. | MALAYSIAN JOURNAL OF LIBRARY & INFORMATION SCIENCE , 2019 , 24 (1) : 59-73 . |
| MLA | Liu, Junwan et al. "The structure and evolution of scientific collaboration from the perspective of symbiosis" . | MALAYSIAN JOURNAL OF LIBRARY & INFORMATION SCIENCE 24 . 1 (2019) : 59-73 . |
| APA | Liu, Junwan , Ding, Kaiyue , Wang, Feifei , Bu, Yi , Maus, Gregory J. . The structure and evolution of scientific collaboration from the perspective of symbiosis . | MALAYSIAN JOURNAL OF LIBRARY & INFORMATION SCIENCE , 2019 , 24 (1) , 59-73 . |
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| GB/T 7714 | Wang Feifei , Jia Chenran , Liu Jiayu et al. Dynamic Assessment of the Academic Influence of Scientific Literature from the Perspective of Altmetrics [C] . 2019 : 2528-2529 . |
| MLA | Wang Feifei et al. "Dynamic Assessment of the Academic Influence of Scientific Literature from the Perspective of Altmetrics" . (2019) : 2528-2529 . |
| APA | Wang Feifei , Jia Chenran , Liu Jiayu , Liu Junwan . Dynamic Assessment of the Academic Influence of Scientific Literature from the Perspective of Altmetrics . (2019) : 2528-2529 . |
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Abstract ：
In order to analyse the gender disparities in scientific research output in the field of economics, this paper selected the Web of Science database as the source database. We collected and screened 257,642 articles written by 130,397 authors from 1933 to 2017 in the field of economics. In this study, we use mathematical statistics and bibliometrics indexes to quantitatively analyse the gap between male and female authors in many aspects, including the output and influence in different level of journals and institutions, the dynamic evolution of output and influence and cooperation modes with gender disparities. In addition, we have analysed the disparities in output and influence of male and female authors among different countries. The results show that male authors dominate in the economics research field according to their high output and influence. However, female authors also show advantage when it comes to the research influence. This study can provide an insight of gender different in economics research.
Keyword ：
economics economics gender disparities gender disparities output output
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| GB/T 7714 | Liu Junwan , Song Yinglu , Yang Sai et al. Gender disparities in the field of economics [C] . 2019 : 932-943 . |
| MLA | Liu Junwan et al. "Gender disparities in the field of economics" . (2019) : 932-943 . |
| APA | Liu Junwan , Song Yinglu , Yang Sai , Sugimoto, Cassidy R. , Lariviere, Vincent . Gender disparities in the field of economics . (2019) : 932-943 . |
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Abstract ：
With the continuous deepening and development of scientific collaboration, relationships within the scientific collaboration network are becoming more and more complex, exhibiting symbiotic characteristics. From the viewpoint of symbiosis, we examine the typical teacher-student relationship using social network analysis. We study the network characteristics of this typical foul' of collaboration based on the resultant published research papers, considering the contribution of symbiosis in the scientific collaboration index to analyze the evolution of the symbiotic relationship between collaborative objects. The results indicate that the symbiotic relationship between teacher and student shows obvious variations from the "old leads young" model; young researchers draw support from the teacher's resources to improve their own level of scientific research with continuous progress and development. Moreover, the collaborative symbiosis degree between teacher and student changes with time.
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| GB/T 7714 | Liu, Junwan , Ding, Kaiyue , Zheng, Xiaomin et al. The structure and evolution of scientific collaboration from the perspective of symbiosis [C] . 2017 : 881-895 . |
| MLA | Liu, Junwan et al. "The structure and evolution of scientific collaboration from the perspective of symbiosis" . (2017) : 881-895 . |
| APA | Liu, Junwan , Ding, Kaiyue , Zheng, Xiaomin , Wang, Feifei . The structure and evolution of scientific collaboration from the perspective of symbiosis . (2017) : 881-895 . |
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| GB/T 7714 | Liu Jun-wan , Zheng Xiao-min , Feng Xiu-zhen et al. Analysis on the Age Distribution of Scientific Elites' Productivity: A study on Academicians of the Chinese Academy of Science [C] . 2015 : 895-896 . |
| MLA | Liu Jun-wan et al. "Analysis on the Age Distribution of Scientific Elites' Productivity: A study on Academicians of the Chinese Academy of Science" . (2015) : 895-896 . |
| APA | Liu Jun-wan , Zheng Xiao-min , Feng Xiu-zhen , Wang Fei-fei . Analysis on the Age Distribution of Scientific Elites' Productivity: A study on Academicians of the Chinese Academy of Science . (2015) : 895-896 . |
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Abstract ：
This study scrutinizes potential author relationships according to the findings based on the tripartite citation analysis. It focuses on Author co-citation analysis (ACA), author bibliographic-coupling analysis (ABCA) and author direct citation analysis (ADCA). By algorithm design and empirical analysis, the deduction from results of ACA, ABCA and ADCA to potential author relationships mining could be probable, and the empirical process would be practicable.
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| GB/T 7714 | Wang, Feifei , Liu, Junwan , Yang, Siluo . Author Relationship Mining based on Tripartite Citation Analysis [C] . 2015 : 261-265 . |
| MLA | Wang, Feifei et al. "Author Relationship Mining based on Tripartite Citation Analysis" . (2015) : 261-265 . |
| APA | Wang, Feifei , Liu, Junwan , Yang, Siluo . Author Relationship Mining based on Tripartite Citation Analysis . (2015) : 261-265 . |
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