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Intermediacy of publications
Citation networks of scientific publications offer fundamental insights into the structure and development of scientific knowledge. We propose a new measure, called intermediacy, for tracing the historical development of scientific knowledge. Given two publications, an older and a more recent one, i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029947/ https://www.ncbi.nlm.nih.gov/pubmed/32218924 http://dx.doi.org/10.1098/rsos.190207 |
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author | Šubelj, Lovro Waltman, Ludo Traag, Vincent van Eck, Nees Jan |
author_facet | Šubelj, Lovro Waltman, Ludo Traag, Vincent van Eck, Nees Jan |
author_sort | Šubelj, Lovro |
collection | PubMed |
description | Citation networks of scientific publications offer fundamental insights into the structure and development of scientific knowledge. We propose a new measure, called intermediacy, for tracing the historical development of scientific knowledge. Given two publications, an older and a more recent one, intermediacy identifies publications that seem to play a major role in the historical development from the older to the more recent publication. The identified publications are important in connecting the older and the more recent publication in the citation network. After providing a formal definition of intermediacy, we study its mathematical properties. We then present two empirical case studies, one tracing historical developments at the interface between the community detection literature and the scientometric literature and one examining the development of the literature on peer review. We show both conceptually and empirically how intermediacy differs from main path analysis, which is the most popular approach for tracing historical developments in citation networks. Main path analysis tends to favour longer paths over shorter ones, whereas intermediacy has the opposite tendency. Compared to the main path analysis, we conclude that intermediacy offers a more principled approach for tracing the historical development of scientific knowledge. |
format | Online Article Text |
id | pubmed-7029947 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-70299472020-03-26 Intermediacy of publications Šubelj, Lovro Waltman, Ludo Traag, Vincent van Eck, Nees Jan R Soc Open Sci Computer Science and Artificial Intelligence Citation networks of scientific publications offer fundamental insights into the structure and development of scientific knowledge. We propose a new measure, called intermediacy, for tracing the historical development of scientific knowledge. Given two publications, an older and a more recent one, intermediacy identifies publications that seem to play a major role in the historical development from the older to the more recent publication. The identified publications are important in connecting the older and the more recent publication in the citation network. After providing a formal definition of intermediacy, we study its mathematical properties. We then present two empirical case studies, one tracing historical developments at the interface between the community detection literature and the scientometric literature and one examining the development of the literature on peer review. We show both conceptually and empirically how intermediacy differs from main path analysis, which is the most popular approach for tracing historical developments in citation networks. Main path analysis tends to favour longer paths over shorter ones, whereas intermediacy has the opposite tendency. Compared to the main path analysis, we conclude that intermediacy offers a more principled approach for tracing the historical development of scientific knowledge. The Royal Society 2020-01-15 /pmc/articles/PMC7029947/ /pubmed/32218924 http://dx.doi.org/10.1098/rsos.190207 Text en © 2020 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Computer Science and Artificial Intelligence Šubelj, Lovro Waltman, Ludo Traag, Vincent van Eck, Nees Jan Intermediacy of publications |
title | Intermediacy of publications |
title_full | Intermediacy of publications |
title_fullStr | Intermediacy of publications |
title_full_unstemmed | Intermediacy of publications |
title_short | Intermediacy of publications |
title_sort | intermediacy of publications |
topic | Computer Science and Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029947/ https://www.ncbi.nlm.nih.gov/pubmed/32218924 http://dx.doi.org/10.1098/rsos.190207 |
work_keys_str_mv | AT subeljlovro intermediacyofpublications AT waltmanludo intermediacyofpublications AT traagvincent intermediacyofpublications AT vaneckneesjan intermediacyofpublications |