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Co-inlinking to a municipal Web space: a webometric and content analysis

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  • Kim Holmberg

    (Åbo Akademi University)

Abstract

It is known that there are significant correlations between linking and geographical patterns. Although interlinking patterns have been studied in various contexts, co-inlinking patterns on the Web have only been studied as indicator of business competitive positions. This research studies the use of co-inlinks to local government Web sites, assesses whether co-inlinking follows geographic patterns and investigates reasons for creating the co-inlinks. Strong evidence was found that co-inlinking is more frequent to municipalities in the same functional region than to municipalities in different functional regions, indicating that this geographic aspect influences co-inlinking, even though geographic co-inlinking was not a strong trend overall. Because the functional regions are created based on cooperation between the municipalities, we have indirectly been able to map cooperation from co-inlinking patterns on the Web. The main reason to create co-inlinking links to municipalities was that the source of the links wanted to show a connection to its region.

Suggested Citation

  • Kim Holmberg, 2010. "Co-inlinking to a municipal Web space: a webometric and content analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 851-862, June.
    • Handle: RePEc:spr:scient:v:83:y:2010:i:3:d:10.1007_s11192-009-0148-1
    DOI: 10.1007/s11192-009-0148-1
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    References listed on IDEAS

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    5. 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.
    6. Kim Holmberg & Mike Thelwall, 2009. "Local government web sites in Finland: A geographic and webometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(1), pages 157-169, April.
    7. Liwen Vaughan, 2004. "Exploring website features for business information," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(3), pages 467-477, November.
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    Cited by:

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    2. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    3. José-Antonio Ontalba-Ruipérez & Enrique Orduna-Malea & Adolfo Alonso-Arroyo, 2016. "Identifying institutional relationships in a geographically distributed public health system using interlinking and co-authorship methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1167-1191, March.
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    5. Bo Yang & Ying Sun, 2013. "An exploration of link-based knowledge map in academic web space," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 239-253, July.
    6. Minjeong Kim & Han Woo Park, 2012. "Measuring Twitter-based political participation and deliberation in the South Korean context by using social network and Triple Helix indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 121-140, January.
    7. 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.
    8. Krzysztof Janc, 2015. "Geography of Hyperlinks-Spatial Dimensions of Local Government Websites," European Planning Studies, Taylor & Francis Journals, vol. 23(5), pages 1019-1037, May.
    9. 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.

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