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Articles

Vol. 2 No. 1 (2015)

Virtual Media Quality Index (W-Index) for Higher Institutions of Education

DOI
https://doi.org/10.15377/2409-9848.2015.02.01.2
Submitted
August 13, 2015
Published
2021-11-24

Abstract

The simplicity and ease of access of its website, has allowed YouTube to be embraced by the whole world and establish itself as the most prominent form of video sharing on earth. YouTube has become a widely used medium for individuals, corporations, and academic institutions alike. In the current work a W-index has been developed and applied to many academic institutions to evaluate the efficacy of the respective YouTube channel(s). This index was the creative product of the senior author who was inspired by the H-index developed by J.E. Hirsch (2005) to evaluate the productivity and impact of a researcher. The W-index will be used to evaluate the quantity and quality of a University’s channel that is different from the traditional staples that define popularity and video effectiveness on YouTube, such as total views. The methodology used would be to see that if this W-index would correlate well to existing indices used for the evaluation of universities. Eventually, the W-index could serve as an indicator of whether or not a university needs to invest time or money into the development of better videos or more videos for their YouTube channel to maximize its impact on the academic community. A correlation between W-Index and three well-established and well-defined cybermetric rankings; US Rank, Impact Rank, and Excellence Rank, is established and used as the basis for the Windex’s usefulness. The establishment of such a correlation indicates that the W-Index can also be used to evaluate the communication efficacy of individuals, despite the lack of any robust ranking system for individuals. The W-Index serves as a good indicator, based on consistent correlation coefficients among ranking systems analyzed, of a university or individual’s success and communication efficacy. Rankings are useful as single numbers that contribute to decision making, simply because of their simplicity.

References

  1. Orduna-Malea E and Ontalba-Ruiperez J. 25 October 2012. Proposal for a multilevel university cybermetric analysis model. An International Journal for all Quantitative Aspects of the Science of Science. Communication in Science and Science Policy 10.1007/s11192-012-0868-5.
  2. YouTube. YouTube n.d. Web. 12 Jan. 2015. .
  3. Vasileiadou E, van den Besselaar P 2006. Linking shallow, linking deep. How scientific intermediaries use the Web for their network of collaborators. ISSN 10(1): 1137-5019.
  4. Hirsch JE. 15 November 2005. An index to quantify an individual’s scientific research output. PNAS 102 (46): 16569-16572. http://dx.doi.org/10.1073/pnas.0507655102
  5. Quesada A. April 2009. Monotonicity and the Hirsch index. Journal of Infometrics 3(2): 158-160. http://dx.doi.org/10.1016/j.joi.2009.01.002
  6. Schreiber M. October 2010. A new family of old Hirsch index variants. Journal of Infometrics 4(4): 647-651. http://dx.doi.org/10.1016/j.joi.2010.05.002
  7. Peterson AM. October 2013. The Z-index: A geometric representation of productivity and impact which accounts for information in the entire rank-citation profile. Journal of Infometrics 7(4): 823-832. http://dx.doi.org/10.1016/j.joi.2013.07.003
  8. Sangwal K. July 2012. On the relationship between citations of publication output and Hirsch index h of authors: conceptualization of tapered Hirsch index hT, circular citation area radius R and citation acceleration. A Journal of Scientometrics 93(3): 987-1004.
  9. United States of America. Ranking Web of Universities. Webometrics. Retrieved January 12, 2015. .
  10. Aguillo IF, Granadino B, Ortega JL, Priesto JA. August 2006. Scientific research activity and communication measured with cybermetrics indicators. Journal of Information Science 57(10): 1296-1296.
  11. Methodology. Ranking Web of Universities. Webometrics n.d. Web. Retrieved 21 Nov. 2014. .
  12. Frequently Asked Questions. Webometrics N.p, Dec 2012. Web. Retrieved 12 Jan 2015. .
  13. Burell QL. January 2007. Hirsch's h-index: A stochastic model. Journal of Infometrics 1(1): 16-25. http://dx.doi.org/10.1016/j.joi.2006.07.001
  14. Kongo T. 1 January 2014.An alternative axiomatization of the Hirsch index. Journal of Infometrics 8(1): 252-258. http://dx.doi.org/10.1016/j.joi.2013.12.005
  15. Schreiber M. April 2013. How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index. Journal of Infometrics 7 (2): 325-329. http://dx.doi.org/10.1016/j.joi.2013.01.001