• DocumentCode
    694796
  • Title

    Revealing Research Themes and their Evolutionary Trends Using Bibliometric Data Based on Strategic Diagrams

  • Author

    Hongqi Han ; Jie Gui ; Shuo Xu

  • Author_Institution
    Inst. of Sci. & Tech. Inf. of China, Beijing, China
  • fYear
    2013
  • fDate
    7-8 Dec. 2013
  • Firstpage
    653
  • Lastpage
    659
  • Abstract
    The paper aims to use strategic diagram technique to detect research themes and reveal their evolutionary trends in a scientific field using bibliometric data under practical application. Keywords are selected not only from author-provided and machine-indexed keywords, but also extracted from the full text so as to eliminate the "indexer effect". The keywords are then clustered to detect research themes, which are classified into four categories in a strategic diagram to reveal the research situations according to their strategic positions. Moreover, the strategic diagrams based on analysis of temporal dynamics are used to find out the thematic evolution through the similarity index to detect similar themes of adjacent phases, and the provenance and influence indexes to evaluate interactions of similar themes. Experimental results showed that the method is effective and useful in revealing research themes and their evolutionary trends in a scientific field.
  • Keywords
    indexing; information retrieval; natural sciences computing; pattern classification; pattern clustering; text analysis; bibliometric data; evolutionary trends; full text extraction; keyword clustering; machine-indexed keywords; research theme classification; research themes; scientific field; similarity index; strategic diagram technique; temporal dynamics; thematic evolution; Density measurement; Indexes; Libraries; Market research; Standards; co-word analysis; strategic diagram; thematic evolution; theme detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
  • Conference_Location
    Guangzhou
  • Type

    conf

  • DOI
    10.1109/ISCC-C.2013.121
  • Filename
    6973666