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Perspective of webometrics

Author

Listed:
  • Lennart Björneborn

    (Royal School of Library and Information Science)

  • Peter Ingwersen

    (Royal School of Library and Information Science)

Abstract

Since the mid-1990s has emerged a new research field, webometrics, investigating the nature and properties of the Web drawing on modern informetric methodologies. The article attempts to point to selected areas of webometric research that demonstrate interesting progress and space for development as well as to some currently less promising areas. Recent investigations of search engine coverage and performance are reviewed as a frame for selected quality and content analyses. Problems with measuring Web Impact Factors (Web-IF) are discussed. Concluding the article, new directions of webometrics are outlined for performing knowledge discovery and issue tracking on the Web, partly based on bibliometric methodologies used in bibliographic and citation databases. In this framework graph theoretic approaches, including path analysis, transversal links, “weak ties” and “small-world” phenomena are integrated.

Suggested Citation

  • Lennart Björneborn & Peter Ingwersen, 2001. "Perspective of webometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(1), pages 65-82, January.
    • Handle: RePEc:spr:scient:v:50:y:2001:i:1:d:10.1023_a:1005642218907
    DOI: 10.1023/A:1005642218907
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    References listed on IDEAS

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    Cited by:

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    2. Sujin Choi & Ji-young Park & Han Woo Park, 2012. "Using social media data to explore communication processes within South Korean online innovation communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 43-56, January.
    3. Gaston Heimeriks & Marianne Hörlesberger & Peter Van Den Besselaar, 2003. "Mapping communication and collaboration in heterogeneous research networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(2), pages 391-413, October.
    4. Daria Maltseva & Vladimir Batagelj, 2020. "iMetrics: the development of the discipline with many names," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 313-359, October.
    5. David Gunnarsson Lorentzen, 2014. "Webometrics benefitting from web mining? An investigation of methods and applications of two research fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 409-445, May.
    6. Benedikt Fecher & Sascha Friesike, 2013. "Open Science: One Term, Five Schools of Thought," RatSWD Working Papers 218, German Data Forum (RatSWD).
    7. Lola García-Santiago & Felix Moya-Anegón, 2009. "Using co-outlinks to mine heterogeneous networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(3), pages 681-702, June.
    8. Cristina Faba-Pérez & Vicente P. Guerrero-Bote & Félix De Moya-Anegón, 2003. "Data mining in a closed Web environment," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 623-640, November.
    9. Xuemei Li & Mike Thelwall & Peter Musgrove & David Wilkinson, 2003. "The relationship between the WIFs or inlinks of Computer Science Departments in UK and their RAE ratings or research productivities in 2001," Scientometrics, Springer;Akadémiai Kiadó, vol. 57(2), pages 239-255, June.
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