Skip to main content
Log in

U.S. academic libraries: understanding their web presence and their relationship with economic indicators

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

The main goal of this research is to analyze the web structure and performance of units and services belonging to U.S. academic libraries in order to check their suitability for webometric studies. Our objectives include studying their possible correlation with economic data and assessing their use for complementary evaluation purposes. We conducted a survey of library homepages, institutional repositories, digital collections, and online catalogs (a total of 374 URLs) belonging to the 100 U.S. universities with the highest total expenditures in academic libraries according to data provided by the National Center for Education Statistics. Several data points were taken and analyzed, including web variables (page count, external links, and visits) and economic variables (total expenditures, expenditures on printed and electronic books, and physical visits). The results indicate that the variety of URL syntaxes is wide, diverse and complex, which produces a misrepresentation of academic libraries’ web resources and reduces the accuracy of web analysis. On the other hand, institutional and web data indicators are not highly correlated. Better results are obtained by correlating total library expenditures with URL mentions measured by Google (r = 0.546) and visits measured by Compete (r = 0.573), respectively. Because correlation values obtained are not highly significant, we estimate such correlations will increase if users can avoid linkage problems (due to the complexity of URLs) and gain direct access to log files (for more accurate data about visits).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Notes

  1. http://www.arl.org/bm~doc/code-of-best-practices-fair-use.pdf. Accessed 26 February 2013.

  2. http://repositories.webometrics.info. Accessed 26 February 2013.

  3. http://www.majesticseo.com. Accessed 26 February 2013.

  4. http://www.opensiteexplorer.org. Accessed 26 February 2013.

  5. http://ahrefs.com. Accessed 26 February 2013.

  6. http://www.compete.com. Accessed 26 February 2013.

  7. http://www.alexa.com. Accessed 26 February 2013.

  8. http://hdl.handle.net/10481/23758. Accessed 26 February 2013.

References

  • Adecannby, J. (2011). Web link analysis of interrelationship between top ten African universities and world universities. Annals of library and information studies, 58(2), 128–138.

    Google Scholar 

  • Aguillo, I. F. (2009). Measuring the institutions’ footprint in the web. Library Hi Tech, 27(4), 540–556.

    Article  Google Scholar 

  • Aguillo, I. F., Ortega, J. L., & Fernández, M. (2008). Webometric Ranking of World Universities: Introduction, methodology, and future developments. Higher education in Europe, 33(2/3), 234–244.

    Google Scholar 

  • Aguillo, I. F., Ortega, J. L., Fernandez, M., & Utrilla, A. M. (2010). Indicators for a webometric ranking of open Access repositories. Scientometrics, 82(3), 477–486.

    Article  Google Scholar 

  • Arakaki, M., & Willet, P. (2009). Webometric analysis of departments of librarianship and information science: A follow-up study. Journal of information science, 35(2), 143–152.

    Article  Google Scholar 

  • Arlitsch, K., & O’Brian, P. S. (2012). Invisible institutional repositories: Addresing the low indexing ratios of IR in Google Scholar. Library Hi Tech, 30(1), 60–81.

    Article  Google Scholar 

  • Bar-Ilan, J. (1999). Search engine results over time—A case study on search engine stability”. Cybermetrics, 2/3. Retrieved February 18, 2013 from http://www.cindoc.csic.es/cybermetrics/articles/v2i1p1.html.

  • Bar-Ilan, J. (2001). Data collection methods on the Web for informetric purposes: A review and analysis. Scientometrics, 50(1), 7–32.

    Article  MathSciNet  Google Scholar 

  • Bermejo, F. (2007). The internet audience: Constitution & measurement. New York: Peter Lang Pub Incorporated.

    Google Scholar 

  • Buigues-Garcia, M., & Gimenez-Chornet, V. (2012). Impact of Web 2.0 on national libraries. International Journal of Information Management, 32(1), 3–10.

    Article  Google Scholar 

  • Chu, H., He, S., & Thelwall, M. (2002). Library and information science schools in Canada and USA: A Webometric perspective. Journal of education for Library and Information Science, 43(2), 110–125.

    Article  Google Scholar 

  • Chua, Alton, Y. K., & Goh, D. H. (2010). A study of Web 2.0 applications in library websites. Library and Information Science Research, 32(3), 203–211.

    Article  Google Scholar 

  • Gallego, I., García, I.-M., & Rodríguez, L. (2009). Universities’ websites: Disclosure practices and the revelation of financial information. The International Journal of Digital Accounting Research, 9(15), 153–192.

    Google Scholar 

  • Gomes, B. & Smith, B. T. (2003). Detecting query-specific duplicate documents. [Patent]. Retrieved February 18, 2013 from http://www.patents.com/Detecting-query-specific-duplicate-documents/US6615209/en-US.

  • Harinarayana, N. S., & Raju, N. V. (2010). Web 2.0 features in university library web sites. Electronic Library, 28(1), 69–88.

    Article  Google Scholar 

  • Lewandowski, D., Wahlig, H., & Meyer-Bautor, G. (2006). The freshness of web search engine databases. Journal of Information Science, 32(2), 131–148.

    Article  Google Scholar 

  • Mahmood, K., & Richardson, J. V, Jr. (2012). Adoption of Web 2.0 in US academic libraries: A survey of ARL library websites. Program, 45(4), 365–375.

    Google Scholar 

  • Orduña-Malea, E., & Ontalba-Ruipérez, J-A. (2012). Selective linking from social platforms to university websites: A case study of the Spanish academic system. Scientometrics. (in press).

  • Ortega, J. L., & Aguillo, I. F. (2009). Mapping World-class universities on the Web. Information Processing and Management, 45(2), 272–279.

    Article  Google Scholar 

  • Ortega, José L. & Aguillo, Isidro F. (2009b). North America Academic Web Space: Multicultural Canada vs. The United States Homogeneity. In: ASIST & ISSI pre-conference symposium on informetrics and scientometrics.

  • Phan, T., Hardesty, L., Sheckells, C., & George, A. (2009). Documentation for the academic libraries survey (ALS) public-use data file: Fiscal year 2008. Washington DC: National Center for Education Statistics. Institute of Education Sciences U.S. Department of Education.

    Google Scholar 

  • Qiu, J., Cheng, J., & Wang, Z. (2004). An analysis of backlinks counts and web impact factors for Chinese university websites. Scientometrics, 60(3), 463–473.

    Article  Google Scholar 

  • Regazzi, J. J. (2012a). Constrained?—An analysis of U.S. Academic Libraries and shifts in spending, staffing and utilization, 1998–2008. College and Research Libraries, 73(5), 449–468.

    Google Scholar 

  • Regazzi, J. J. (2012b). Comparing Academic Library Spending with Public Libraries, Public K-12 Schools, Higher Education Public Institutions, and Public Hospitals Between 1998–2008. Journal of Academic Librarianship, 38(4), 205–216.

    Article  Google Scholar 

  • Rousseau, R. (1999). Daily time series of common single word searches in AltaVista and NorthernLight. Cybermetrics, 2/3. Retrieved February 18, 2013 from http://www.cindoc.csic.es/cybermetrics/articles/v2i1p2.html.

  • Sato, S., & Itsumura, H. (2011). How do people use open access papers in non-academic activities? A link analysis of papers deposited in institutional repositories. Library, Information and Media Studies, 9(1), 51–64.

    Google Scholar 

  • Scholze, F. (2007). Measuring research impact in an open access environment. Liber Quarterly: The Journal of European Research Libraries, 17(1–4), 220–232.

    Google Scholar 

  • Smith, A. G. (2011). Wikipedia and institutional repositories: An academic symbiosis? In: Proceedings of the ISSI 2011 conference. Durban, South Africa, 4–7 July 2011. Retrieved February 18, 2013 from http://www.vuw.ac.nz/staff/alastair_smith/publns/SmithAG2011_ISSI_paper.pdf.

  • Smith, A.G. (2012). Webometric evaluation of institutional repositories. In: Proceedings of the 8th international conference on webometrics informetrics and scientometrics & 13th collnet meeting. Seoul (Korea), 722–729.

  • Smith, A., & Thelwall, M. (2002). Web impact factors for Australasian Universities. Scientometrics, 54(3), 363–380.

    Article  Google Scholar 

  • Tang, R., & Thelwall, M. (2008). A hyperlink analysis of US public and academic libraries’ web sites. Library Quarterly, 78(4), 419–435.

    Article  Google Scholar 

  • Thelwall, M. (2008). Extracting accurate and complete results from search engines: Case study Windows Live. Journal of the American Society for Information Science and Technology, 59(1), 38–50.

    Article  Google Scholar 

  • Thelwall, M. (2009). Introduction to webometrics: Quantitative web research for the social sciences. San Rafael: Morgan & Claypool.

    Google Scholar 

  • Thelwall, M., & Sud, P. (2011). A comparison of methods for collecting web citation data for academic organisations. Journal of the American Society for Information Science and Technology, 62(8), 1488–1497.

    Article  Google Scholar 

  • Thelwall, M., Sud, P., & Wilkinson, D. (2012). Link and co-inlink network diagrams with URL citations or title mentions. Journal of the American Society for Information Science and Technology, 63(10), 1960–1972.

    Article  Google Scholar 

  • Thelwall, M., & Zuccala, A. (2008). A University-centred European Union link analysis. Scientometrics, 75(3), 407–442.

    Article  Google Scholar 

  • Uyar, A. (2009a). Google stemming mechanisms. Journal of Information Science, 35(5), 499–514.

    Google Scholar 

  • Uyar, A. (2009b). Investigation of the accuracy of search engine hit counts. Journal of Information Science, 35(4), 469–480.

    Article  MathSciNet  Google Scholar 

  • Zuccala, A., Thelwall, M., Oppenheim, C., & Dhiensa, R. (2007). Web intelligence analyses of digital libraries: A case study of the National Electronic Library for Health (NeLH). Journal of Documentation, 63(4), 558–589.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Enrique Orduña-Malea.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Orduña-Malea, E., Regazzi, J.J. U.S. academic libraries: understanding their web presence and their relationship with economic indicators. Scientometrics 98, 315–336 (2014). https://doi.org/10.1007/s11192-013-1001-0

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-013-1001-0

Keywords

Navigation