A comparison of journal similarity across six disciplines using citing discipline analysis |
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| Institution: | 1. School of Information Management, Wuhan University, Wuhan 430072, China;2. School of Economics and Management, Beijing University of Technology, Beijing 100024, China;1. School of Public Health, Taipei Medical University, 250 Wu-Hsing Street, Taipei 11014, Taiwan;2. Trend Research Centre, Asia University, 500, Lioufeng Road, Wufeng, Taichung County 41354, Taiwan;1. University Library, Stockholm University, SE 106 91 Stockholm, Sweden;2. Centre for Science and Technology Studies (CWTS), Leiden University, P.O. Box 905, 2300 AX Leiden, The Netherlands;1. Centre for R&D Monitoring (ECOOM), Faculty of Social Sciences, University of Antwerp, Middelheimlaan 1, B-2020 Antwerp, Belgium;2. Informatie- en Bibliotheekwetenschap, University of Antwerp, Venusstraat 35, B-2000 Antwerp, Belgium;3. KU Leuven, Dept. of Mathematics, B-3000 Leuven, Belgium;4. Antwerp Maritime Academy, Noordkasteel Oost 6, B-2030 Antwerp, Belgium |
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| Abstract: | A similarity comparison is made between 120 journals from five allied Web of Science disciplines (Communication, Computer Science-Information Systems, Education & Educational Research, Information Science & Library Science, Management) and a more distant discipline (Geology) across three time periods using a novel method called citing discipline analysis that relies on the frequency distribution of Web of Science Research Areas for citing articles. Similarities among journals are evaluated using multidimensional scaling with hierarchical cluster analysis and Principal Component Analysis. The resulting visualizations and groupings reveal clusters that align with the discipline assignments for the journals for four of the six disciplines, but also greater overlaps among some journals for two of the disciplines or categorizations that do not necessarily align with their assigned disciplines. Some journals categorized into a single given discipline were found to be more closely aligned with other disciplines and some journals assigned to multiple disciplines more closely aligned with only one of the assigned disciplines. The proposed method offers a complementary way to more traditional methods such as journal co-citation analysis to compare journal similarity using data that are readily available through Web of Science. |
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| Keywords: | Journal similarity Citer analysis Citation analysis Citing discipline analysis |
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