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A Trend Analysis of Domain-Specific Literatures with Content and Co-author Network Similarity

  • Christopher C. Yang
  • Xuning Tang
  • Min Song
  • Suyeon Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7634)

Abstract

By examining scientific literatures over a period of time, we see new topics being developed and new contributing researchers are participating. In this work, we explore the content similarity and co-authorship network similarity to gain a better understanding of the scientific literature development. In particular, we are interested in three domains namely, database (DB), information retrieval (IR), and World Wide Web (W3), as well as the journal Information Processing & Management. We finds that Information Processing & Management has a trend of increasing similarity with IR and W3 instead of DB.

Keywords

content analysis co-authorship network scientific dynamics 

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References

  1. 1.
    Ding, Y.: Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks. Journal of Informetrics 5(1), 187–203 (2011)CrossRefGoogle Scholar
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    Garfield, E.: Citation analysis as a tool in journal evaluation. Science 178, 471–479 (1972)CrossRefGoogle Scholar
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    Small, H.: Co-citation in scientific literature: New measure of relationship between two documents. Journal of the American Society for Information Science (1973)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Christopher C. Yang
    • 1
  • Xuning Tang
    • 1
  • Min Song
    • 2
  • Suyeon Kim
    • 2
  1. 1.College of Information Science and TechnologyDrexel UniversityPhiladelphiaUSA
  2. 2.Department of Library and Information ScienceYonsei UniversitySeoulKorea

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