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  • × author_ss:"Strotmann, A."
  • × theme_ss:"Informetrie"
  1. Zhao, D.; Strotmann, A.: ¬The knowledge base and research front of information science 2006-2010 : an author cocitation and bibliographic coupling analysis (2014) 0.01
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    Abstract
    This study continues a long history of author cocitation analysis (and more recently, author bibliographic coupling analysis) of the intellectual structure of information science (IS) into the time period 2006 to 2010 (IS 2006-2010). We find that web technologies continue to drive developments, especially at the research front, although perhaps more indirectly than before. A broadening of perspectives is visible in IS 2006-2010, where network science becomes influential and where full-text analysis methods complement traditional computer science influences. Research in the areas of the h-index and mapping of science appears to have been highlights of IS 2006-2011. This study tests and confirms a forecast made previously by comparing knowledge-base and research-front findings for IS 2001-2005, which expected both the information retrieval (IR) systems and webometrics specialties to shrink in 2006 to 2010. A corresponding comparison of the knowledge base and research front of IS 2006-2010 suggests a continuing decline of the IR systems specialty in the near future, but also a considerable (re)growth of the webometrics area after a period of decline from 2001 to 2005 and 2006 to 2010, with the latter due perhaps in part to its contribution to an emerging web science.
  2. Zhao, D.; Strotmann, A.: Intellectual structure of information science 2011-2020 : an author co-citation analysis (2022) 0.01
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    Abstract
    Purpose This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011-2020. It also examines changes in this structure from 2006-2010 through 2011-2015 to 2016-2020. Results will contribute to a better understanding of the information science research field. Design/methodology/approach The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011-2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor. Findings The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011-2015 but shared dominance with information behavior during 2016-2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016-2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011-2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016-2020. Originality/value Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.