Co-Authorship Network Analysis in Industrial Ecology Research Community / Kim Dzhun Beum, P. Charles

Уровень набора: Journal of Industrial EcologyОсновной Автор-лицо: Kim Dzhun Beum, geochemist, Associate Professor of Tomsk Polytechnic University, 1974-Альтернативный автор-лицо: Charles, P., PerezКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет (ТПУ), Институт природных ресурсов (ИПР), Кафедра геоэкологии и геохимии (ГЭГХ)Язык: английский.Страна: .Резюме или реферат: Many scientific collaboration networks have been extensively studied from different perspectives, such as network degree analysis or centrality. However, there has been little study of the scientific collaboration network in the industrial ecology (IE) research domain and community. In this study therefore, we collected co-authorship keywords and related data from 1,032 publications between 1997 and 2012 from the most influential journal on the topic: the Journal of Industrial Ecology. An evaluation of publications in terms of network characteristics was conducted. Journal characteristics, such as publications by each author, number of co-authors per paper, and keywords, were identified. Further, we developed a co-authorship network and maps with network centrality analysis, components, and cluster analysis. The results of this study clearly show the main topics of the science, structure of scientific collaboration, and status of individual researchers within the IE research community..Аудитория: .Тематика: электронный ресурс | труды учёных ТПУ | bibliometrics | co-authorship | industrial ecology | information | visualization Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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Many scientific collaboration networks have been extensively studied from different perspectives, such as network degree analysis or centrality. However, there has been little study of the scientific collaboration network in the industrial ecology (IE) research domain and community. In this study therefore, we collected co-authorship keywords and related data from 1,032 publications between 1997 and 2012 from the most influential journal on the topic: the Journal of Industrial Ecology. An evaluation of publications in terms of network characteristics was conducted. Journal characteristics, such as publications by each author, number of co-authors per paper, and keywords, were identified. Further, we developed a co-authorship network and maps with network centrality analysis, components, and cluster analysis. The results of this study clearly show the main topics of the science, structure of scientific collaboration, and status of individual researchers within the IE research community.

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