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Link and co‐inlink network diagrams with URL citations or title mentions

Author

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  • Mike Thelwall
  • Pardeep Sud
  • David Wilkinson

Abstract

Webometric network analyses have been used to map the connectivity of groups of websites to identify clusters, important sites or overall structure. Such analyses have mainly been based upon hyperlink counts, the number of hyperlinks between a pair of websites, although some have used title mentions or URL citations instead. The ability to automatically gather hyperlink counts from Yahoo! ceased in April 2011 and the ability to manually gather such counts was due to cease by early 2012, creating a need for alternatives. This article assesses URL citations and title mentions as possible replacements for hyperlinks in both binary and weighted direct link and co‐inlink network diagrams. It also assesses three different types of data for the network connections: hit count estimates, counts of matching URLs, and filtered counts of matching URLs. Results from analyses of U.S. library and information science departments and U.K. universities give evidence that metrics based upon URLs or titles can be appropriate replacements for metrics based upon hyperlinks for both binary and weighted networks, although filtered counts of matching URLs are necessary to give the best results for co‐title mention and co‐URL citation network diagrams.

Suggested Citation

  • Mike Thelwall & Pardeep Sud & David Wilkinson, 2012. "Link and co‐inlink network diagrams with URL citations or title mentions," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(4), pages 805-816, April.
  • Handle: RePEc:bla:jamist:v:63:y:2012:i:4:p:805-816
    DOI: 10.1002/asi.21709
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    Cited by:

    1. Enrique Orduña-Malea, 2021. "Dot-science top level domain: Academic websites or dumpsites?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3565-3591, April.
    2. Enrique Orduña-Malea & John J. Regazzi, 2014. "U.S. academic libraries: understanding their web presence and their relationship with economic indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 315-336, January.
    3. Natalia Sánchez-Arrieta & Rafael A. González & Antonio Cañabate & Ferran Sabate, 2021. "Social Capital on Social Networking Sites: A Social Network Perspective," Sustainability, MDPI, vol. 13(9), pages 1-35, May.
    4. George A. Barnett & Han Woo Park & Ke Jiang & Chuan Tang & Isidro F. Aguillo, 2014. "A multi-level network analysis of web-citations among the world’s universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 5-26, April.
    5. Srijana Acharya & Han Woo Park, 2017. "Open data in Nepal: a webometric network analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1027-1043, May.
    6. Pardeep Sud & Mike Thelwall, 2014. "Linked title mentions: a new automated link search candidate," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1831-1849, December.
    7. Amalia Mas-Bleda & Mike Thelwall & Kayvan Kousha & Isidro F. Aguillo, 2014. "Do highly cited researchers successfully use the social web?," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 337-356, October.
    8. Junwei Ma & Jianhua Wang & Philip Szmedra, 2019. "Sustainable Competitive Position of Mobile Communication Companies: Comprehensive Perspectives of Insiders and Outsiders," Sustainability, MDPI, vol. 11(7), pages 1-15, April.

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