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Interplay between success and patterns of human collaboration: case study of a Thai Research Institute

Networks of collaboration are notoriously complex and the mechanisms underlying their evolution, although of high interest, are still not fully understood. In particular, collaboration networks can be used to model the interactions between scientists and analyze the circumstances that lead to succes...

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Autores principales: Fiscarelli, Antonio Maria, Brust, Matthias R., Bouffanais, Roland, Piyatumrong, Apivadee, Danoy, Grégoire, Bouvry, Pascal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801490/
https://www.ncbi.nlm.nih.gov/pubmed/33431924
http://dx.doi.org/10.1038/s41598-020-79447-z
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author Fiscarelli, Antonio Maria
Brust, Matthias R.
Bouffanais, Roland
Piyatumrong, Apivadee
Danoy, Grégoire
Bouvry, Pascal
author_facet Fiscarelli, Antonio Maria
Brust, Matthias R.
Bouffanais, Roland
Piyatumrong, Apivadee
Danoy, Grégoire
Bouvry, Pascal
author_sort Fiscarelli, Antonio Maria
collection PubMed
description Networks of collaboration are notoriously complex and the mechanisms underlying their evolution, although of high interest, are still not fully understood. In particular, collaboration networks can be used to model the interactions between scientists and analyze the circumstances that lead to successful research. This task is not trivial and conventional metrics, based on number of publications and number of citations of individual authors, may not be sufficient to provide a deep insight into the factors driving scientific success. However, network analysis techniques based on centrality measures and measures of the structural properties of the network are promising to that effect. In recent years, it has become evident that most successful research works are achieved by teams rather than individual researchers. Therefore, researchers have developed a keen interest in the dynamics of social groups. In this study, we use real world data from a Thai computer technology research center, where researchers collaborate on different projects and team up to produce a range of artifacts. For each artifact, a score that measures quality of research is available and shared between the researchers that contributed to its creation, according to their percentage of contribution. We identify several measures to quantify productivity and quality of work, as well as centrality measures and structural measures. We find that, at individual level, centrality metrics are linked to high productivity and quality of work, suggesting that researchers who cover strategic positions in the network of collaboration are more successful. At the team level, we show that the evolution in time of structural measures are also linked to high productivity and quality of work. This result suggests that variables such as team size, turnover rate, team compactness and team openness are critical factors that must be taken into account for the success of a team. The key findings of this study indicate that the success of a research institute needs to be assessed in the context of not just researcher or team level, but also on how the researchers engage in collaboration as well as on how teams evolve.
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spelling pubmed-78014902021-01-12 Interplay between success and patterns of human collaboration: case study of a Thai Research Institute Fiscarelli, Antonio Maria Brust, Matthias R. Bouffanais, Roland Piyatumrong, Apivadee Danoy, Grégoire Bouvry, Pascal Sci Rep Article Networks of collaboration are notoriously complex and the mechanisms underlying their evolution, although of high interest, are still not fully understood. In particular, collaboration networks can be used to model the interactions between scientists and analyze the circumstances that lead to successful research. This task is not trivial and conventional metrics, based on number of publications and number of citations of individual authors, may not be sufficient to provide a deep insight into the factors driving scientific success. However, network analysis techniques based on centrality measures and measures of the structural properties of the network are promising to that effect. In recent years, it has become evident that most successful research works are achieved by teams rather than individual researchers. Therefore, researchers have developed a keen interest in the dynamics of social groups. In this study, we use real world data from a Thai computer technology research center, where researchers collaborate on different projects and team up to produce a range of artifacts. For each artifact, a score that measures quality of research is available and shared between the researchers that contributed to its creation, according to their percentage of contribution. We identify several measures to quantify productivity and quality of work, as well as centrality measures and structural measures. We find that, at individual level, centrality metrics are linked to high productivity and quality of work, suggesting that researchers who cover strategic positions in the network of collaboration are more successful. At the team level, we show that the evolution in time of structural measures are also linked to high productivity and quality of work. This result suggests that variables such as team size, turnover rate, team compactness and team openness are critical factors that must be taken into account for the success of a team. The key findings of this study indicate that the success of a research institute needs to be assessed in the context of not just researcher or team level, but also on how the researchers engage in collaboration as well as on how teams evolve. Nature Publishing Group UK 2021-01-11 /pmc/articles/PMC7801490/ /pubmed/33431924 http://dx.doi.org/10.1038/s41598-020-79447-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Fiscarelli, Antonio Maria
Brust, Matthias R.
Bouffanais, Roland
Piyatumrong, Apivadee
Danoy, Grégoire
Bouvry, Pascal
Interplay between success and patterns of human collaboration: case study of a Thai Research Institute
title Interplay between success and patterns of human collaboration: case study of a Thai Research Institute
title_full Interplay between success and patterns of human collaboration: case study of a Thai Research Institute
title_fullStr Interplay between success and patterns of human collaboration: case study of a Thai Research Institute
title_full_unstemmed Interplay between success and patterns of human collaboration: case study of a Thai Research Institute
title_short Interplay between success and patterns of human collaboration: case study of a Thai Research Institute
title_sort interplay between success and patterns of human collaboration: case study of a thai research institute
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801490/
https://www.ncbi.nlm.nih.gov/pubmed/33431924
http://dx.doi.org/10.1038/s41598-020-79447-z
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