Advertisement

Electronic Markets

, Volume 29, Issue 3, pp 519–532 | Cite as

Online video impact of world class universities

  • Angel Meseguer-Martinez
  • Alejandro Ros-GalvezEmail author
  • Alfonso Rosa-Garcia
  • Jose Antonio Catalan-Alarcon
Research Paper

Abstract

YouTube has become the standard social network for the dissemination of university multimedia content, but the impact of academic online videos has been scarcely researched. This study covers this gap and provides a new dimension to evaluate university performance. Data and statistics of 416 YouTube accounts and ca. 190,000 online videos of world class universities are gathered. The H-index is adapted to quantify the online video impact, universities are ranked accordingly and the correlates of impact are analyzed. The H-based ranking of online video impact is closely related to standard rankings of world class universities, with a stronger relation than that with other online video related metrics. Research productivity and online video orientation of a university are robustly related to online video impact, whereas teaching, university size and geographical location are not.

Keywords

Online video World class universities Impact H-index Altmetrics Rankings 

JEL classification

A20 I20 

Notes

Acknowledgements

Alfonso Rosa-Garcia acknowledges support from project ECO2016-76178-P from the Spanish Ministry of Economy, Industry and Competitiveness.

Supplementary material

12525_2018_315_MOESM1_ESM.docx (33 kb)
Appendix A (DOCX 33 kb)
12525_2018_315_MOESM2_ESM.docx (28 kb)
Appendix B (DOCX 28 kb)

References

  1. Academic Ranking of World Universities, ARWU (2015), available at: http://www.shanghairanking.com/ARWU2015.html
  2. 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), 233–244.Google Scholar
  3. Aguillo, I. F., Bar-Ilan, J., Levene, M., & Ortega, J. L. (2010). Comparing university rankings. Scientometrics, 85(1), 243–256.Google Scholar
  4. Ajjan, H., & Hartshorne, R. (2008). Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests. The Internet and Higher Education, 11(2), 71–80.Google Scholar
  5. Ann Voss, K., & Kumar, A. (2013). The value of social media: Are universities successfully engaging their audience? Journal of Applied Research in Higher Education, 5(2), 156–172.Google Scholar
  6. Balakrishnan, J., & Griffiths, M. D. (2017). Social media addiction: What is the role of content in YouTube? Journal of Behavioral Addictions, 6(3), 364–377.Google Scholar
  7. Belanger, C. H., Bali, S., & Longden, B. (2014). How Canadian universities use social media to brand themselves. Tertiary Education and Management, 20(1), 14–29.Google Scholar
  8. Berk, R. A. (2009). Multimedia teaching with video clips: TV, movies, YouTube, and mtvU in the college classroom. International Journal of Technology in Teaching and Learning, 5(1), 1–21.Google Scholar
  9. Blumler, J. G., & Katz, E. (1974). The uses of mass communications: Current perspectives on gratifications research. Newbury Park: Sage.Google Scholar
  10. Borghol, Y., Mitra, S., Ardon, S., Carlsson, N., Eager, D., & Mahanti, A. (2011). Characterizing and modelling popularity of user-generated videos. Performance Evaluation, 68(11), 1037–1055.Google Scholar
  11. Borghol, Y., Ardon, S., Carlsson, N., Eager, D., & Mahanti, A. (2012). The untold story of the clones: Content-agnostic factors that impact YouTube video popularity. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 1186–1194.Google Scholar
  12. Bowman, N. A., & Bastedo, M. N. (2011). Anchoring effects in world university rankings: Exploring biases in reputation scores. Higher Education, 61(4), 431–444.Google Scholar
  13. Braun, T., Glänzel, W., & Schubert, A. (2006). A Hirsch-type index for journals. Scientometrics, 69(1), 169–173.Google Scholar
  14. Brech, F. M., Messer, U., Vander Schee, B. A., Rauschnabel, P. A., & Ivens, B. S. (2017). Engaging fans and the community in social media: Interaction with institutions of higher education on Facebook. Journal of Marketing for Higher Education, 27(1), 112–130.Google Scholar
  15. Brodersen, A., Scellato, S., & Wattenhofer, M. (2012). YouTube around the world: Geographic popularity of videos. Proceedings of the 21st international conference on World Wide Web, 241–250.Google Scholar
  16. Çakır, M. P., Acartürk, C., Alaşehir, O., & Çilingir, C. (2015). A comparative analysis of global and national university ranking systems. Scientometrics, 103(3), 813–848.Google Scholar
  17. Cha, M., Kwak, H., Rodriguez, P., Ahn, Y. Y., & Moon, S. (2007). I tube, you tube, everybody tubes: Analyzing the world's largest user generated content video system. Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, 1–14.Google Scholar
  18. Cha, M., Kwak, H., Rodriguez, P., Ahn, Y. Y., & Moon, S. (2009). Analyzing the video popularity characteristics of large-scale user generated content systems. IEEE/ACM Transactions on Networking (TON), 17(5), 1357–1370.Google Scholar
  19. Chatzopoulou, G., Sheng, C., & Faloutsos, M. (2010). A first step towards understanding popularity in YouTube. INFOCOM IEEE Conference on Computer Communications Workshops, 1–6.Google Scholar
  20. Chen, L., Zhou, Y., & Chiu, D. M. (2015). Analysis and detection of fake views in online video services. ACM Transactions on Multimedia Computing, Communications, and Applications, 11(44), 1–20.Google Scholar
  21. Cheng, X., Liu, J., & Dale, C. (2013). Understanding the characteristics of internet short video sharing: A YouTube-based measurement study. IEEE Transactions on Multimedia, 15(5), 1184–1194.Google Scholar
  22. Chiang, H. S., & Hsiao, K. L. (2015). YouTube stickiness: The needs, personal, and environmental perspective. Internet Research, 25(1), 85–106.Google Scholar
  23. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Lillington: Routledge.Google Scholar
  24. Costas, R., Zahedi, Z., & Wouters, P. (2015). Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. Journal of the Association for Information Science and Technology, 66(10), 2003–2019.Google Scholar
  25. Crane, R., & Sornette, D. (2008). Viral, Quality, and Junk Videos on YouTube: Separating Content from Noise in an Information-Rich Environment. AAAI Spring Symposium: Social Information Processing, 18–20.Google Scholar
  26. Dijkmans, C., Kerkhof, P., & Beukeboom, C. J. (2015). A stage to engage: Social media use and corporate reputation. Tourism Management, 47, 58–67.Google Scholar
  27. Fernandez-Cano, A., & Fernández-Guerrero, I. M. (2017). A multivariate model for evaluating emergency medicine journals. Scientometrics, 110(2), 991–1003.Google Scholar
  28. Figueiredo, F., Benevenuto, F., & Almeida, J. M. (2011). The tube over time: characterizing popularity growth of youtube videos. Proceedings of the fourth ACM international conference on Web search and data mining, 745–754.Google Scholar
  29. Figueiredo, F. (2013). On the prediction of popularity of trends and hits for user generated videos. Proceedings of the sixth ACM international conference on Web search and data mining, 741–746.Google Scholar
  30. Garfield, E. (1955). Citation indexes for science: A new dimension in documentation through association of ideas. Science, 122(3159), 108–111.Google Scholar
  31. Gilroy, M. (2010). Higher education migrates to YouTube and social networks. Education Digest, 75(7), 18–22.Google Scholar
  32. Guo, P. J., Kim, J., & Rubin, R. (2014). How video production affects student engagement: An empirical study of mooc videos. Proceedings of the first ACM conference on Learning @ Scale, 41–50.Google Scholar
  33. Guzmán, A. P., & Del Moral Pérez, M. E. (2014). Trends in use of YouTube: Optimizing the strategic communication of Ibero-American universities. Observatorio, 8(1), 69–94.Google Scholar
  34. Haustein, S., Peters, I., Sugimoto, C. R., Thelwall, M., & Larivière, V. (2014). Tweeting biomedicine: An analysis of tweets and citations in the biomedical literature. Journal of the Association for Information Science and Technology, 65(4), 656–669.Google Scholar
  35. Haustein, S., Costas, R., & Larivière, V. (2015). Characterizing social media metrics of scholarly papers: The effect of document properties and collaboration patterns. PLoS One, 10(3), e0120495.Google Scholar
  36. Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569–16572.Google Scholar
  37. Holmberg, K. (2015). Online attention of universities in Finland: Are the bigger universities bigger online too? Procs of ISSI 2015-15th Intl conf of the International Society for Scientometrics and Informetrics, 83–88.Google Scholar
  38. Hovden, R. (2013). Bibliometrics for internet media: Applying the h-index to YouTube. Journal of the American Society for Information Science and Technology, 64(11), 2326–2331.Google Scholar
  39. Hsu, C. L., Chuan-Chuan Lin, J., & Chiang, H. S. (2013). The effects of blogger recommendations on customers’ online shopping intentions. Internet Research, 23(1), 69–88.Google Scholar
  40. Jiang, L., Miao, Y., Yang, Y., Lan, Z., & Hauptmann, A. G. (2014). Viral video style: A closer look at viral videos on YouTube. Proceedings of International Conference on Multimedia Retrieval, 193.Google Scholar
  41. Khan, M. L. (2017). Social media engagement: What motivates user participation and consumption on YouTube? Computers in Human Behavior, 66, 236–247.Google Scholar
  42. Khan, G. F., & Vong, S. (2014). Virality over YouTube: An empirical analysis. Internet Research, 24(5), 629–647.Google Scholar
  43. Kousha, K., Thelwall, M., & Abdoli, M. (2012). The role of online videos in research communication: A content analysis of YouTube videos cited in academic publications. Journal of the American Society for Information Science and Technology, 63(9), 1710–1727.Google Scholar
  44. Koz, O. (2013), “Social media policies in U.S. universities”, Texas social media research institute / social media conference, available at: http://works.bepress.com/olga_koz/2/
  45. Laakso, M., Lindman, J., Shen, C., Nyman, L., & Björk, B. C. (2017). Research output availability on academic social networks: Implications for stakeholders in academic publishing. Electronic Markets, 27(2), 125–133.Google Scholar
  46. Lazaridis, T. (2010). Ranking university departments using the mean h-index. Scientometrics, 82(2), 211–216.Google Scholar
  47. Liao, W. C. (2012). Using short videos in teaching a social science subject: Values and challenges. Journal of the NUS Teaching Academy, 2(1), 42–55.Google Scholar
  48. Liu, N. C., & Cheng, Y. (2005). The academic ranking of world universities. Higher Education in Europe, 30(2), 127–136.Google Scholar
  49. Lovari, A., & Giglietto, F. (2012). Social Media and Italian Universities: An Empirical Study on the Adoption and Use of Facebook, Twitter and YouTube. Available at: http://ssrn.com/abstract=1978393 or doi:  https://doi.org/10.2139/ssrn.1978393.
  50. Manca, S., & Ranieri, M. (2016). “Yes for sharing, no for teaching!”: Social media in academic practices. The Internet and Higher Education, 29, 63–74.Google Scholar
  51. Marciel, M., Cuevas, R., Banchs, A., Gonzalez, R., Traverso, S., Ahmed, M., & Azcorra, A. (2016). Understanding the detection of view fraud in video content portals. WWW '16 Proceedings of the 25th international conference on World Wide Web, 357–368.Google Scholar
  52. Meseguer-Martinez, A., Ros-Galvez, A., & Rosa-Garcia, A. (2017). Satisfaction with online teaching videos: A quantitative approach. Innovations in Education and Teaching International, 54(1), 62–67.Google Scholar
  53. Moed, H. F. (2017). A critical comparative analysis of five world university rankings. Scientometrics, 110(2), 967–990.Google Scholar
  54. Moran, M., Seaman, J., & Tinti-kane, H. (2011). Teaching, learning, and sharing: How today’s higher education faculty use social media. Research report published by Pearson, The Babson Survey Research Group, and Converseon. Available at: http://www3.babson.edu/ESHIP/research-publications/upload/Teaching_Learning_and_Sharing.pdf.
  55. Oh, S., Baek, H., & Ahn, J. (2017). Predictive value of video-sharing behavior: Sharing of movie trailers and box-office revenue. Internet Research, 27(3), 691–708.Google Scholar
  56. Olcay, G. A., & Bulu, M. (2016). Is measuring the knowledge creation of universities possible? A review of university rankings. Technological Forecasting and Social Change, forthcoming.Google Scholar
  57. Pan, X., Yan, E., & Hua, W. (2016). Science communication and dissemination in different cultures: An analysis of the audience for TED videos in China and abroad. Journal of the Association for Information Science and Technology, 67(6), 1473–1486.Google Scholar
  58. Pathak, B. K. (2016). Emerging online educational models and the transformation of traditional universities. Electronic Markets, 26(4), 315–321.Google Scholar
  59. Piro, F. N., Hovdhaugen, E., Elken, M., Sivertsen, G., Benner, M., & Stensaker, B. (2014). Nordiske universiteter og internasjonale universitetsrangeringer: Hva forklarer nordiske plasseringer og hvordan forholder universitetene seg til rangeringene? NIFU rapport 25/2014. Oslo: NIFU.Google Scholar
  60. Priem, J., & Hemminger, B. M. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday, 15(7).Google Scholar
  61. Priem, J., Piwowar, H. A., & Hemminger, B. M. (2012). Altmetrics in the wild: Using social media to explore scholarly impact. arXiv preprint arXiv:1203.4745.Google Scholar
  62. Ratkiewicz, J., Conover, M., Meiss, M. R., Gonçalves, B., Flammini, A., & Menczer, F. (2011). Detecting and tracking political abuse in social media, Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, 297–304.Google Scholar
  63. Ravenscroft, J., Liakata, M., Clare, A., & Duma, D. (2017). Measuring scientific impact beyond academia: An assessment of existing impact metrics and proposed improvements. PLoS One, 12(3), e0173152.Google Scholar
  64. Rosenthal, S. (2017). Motivations to seek science videos on YouTube: Free-choice learning in a connected society. International Journal of Science Education, Part B, 1–18.Google Scholar
  65. Safón, V. (2013). What do global university rankings really measure? The search for the X factor and the X entity. Scientometrics, 97(2), 223–244.Google Scholar
  66. Saisana, M., d’Hombres, B., & Saltelli, A. (2011). Rickety numbers: Volatility of university rankings and policy implications. Research Policy, 40(1), 165–177.Google Scholar
  67. Savin, N. E. (1980). The Bonferroni and the Scheffe multiple comparison procedures. The Review of Economic Studies, 47(1), 255–273.Google Scholar
  68. Simpson, W., & Greenfield, H. (2009). IPTV and internet video: Expanding the reach of television broadcasting (2nd ed.). New York and London: Focal Press.Google Scholar
  69. Statisticbrain (2016). YouTube company statistics. Available at: http://www.statisticbrain.com/youtube-statistics
  70. Sugimoto, C. R., Thelwall, M., Larivière, V., Tsou, A., Mongeon, P., & Macaluso, B. (2013). Scientists popularizing science: Characteristics and impact of TED talk presenters. PLoS One, 8(4), e62403.Google Scholar
  71. Susarla, A., Oh, J. H., & Tan, Y. (2012). Social networks and the diffusion of user-generated content: Evidence from YouTube. Information Systems Research, 23(1), 23–41.Google Scholar
  72. Szabo, G., & Huberman, B. A. (2010). Predicting the popularity of online content. Communications of the ACM, 53(8), 80–88.Google Scholar
  73. Szentirmai, L., & Radács, L. (2013). World university rankings qualify teaching and primarily research. ICETA 2013, 11th IEEE International Conference on Emerging eLearning Technologies and Applications, 369–374.Google Scholar
  74. Thelwall, M., Kousha, K., Weller, K., & Puschmann, C. (2012). Chapter 9. Assessing the impact of online academic videos. In G. Widén & K. Holmberg (Eds.), Social information research (library and information science, volume 5) (pp. 195–213). Emerald Group Publishing Limited.Google Scholar
  75. Thelwall, M., Haustein, S., Larivière, V., & Sugimoto, C. R. (2013). Do altmetrics work? Twitter and ten other social web services. PLoS One, 8(5), e64841.Google Scholar
  76. Thoma, B., Sanders, J. L., Lin, M., Paterson, Q. S., Steeg, J., & Chan, T. M. (2015). The social media index: Measuring the impact of emergency medicine and critical care websites. Western Journal of Emergency Medicine, 16(2), 242–249.Google Scholar
  77. Times Higher Education, THE (2015). Available at: https://www.timeshighereducation.com/world-university-rankings/2016
  78. Toven-Lindsey, B., Rhoads, R. A., & Lozano, J. B. (2015). Virtually unlimited classrooms: Pedagogical practices in massive open online courses. The Internet and Higher Education, 24, 1–12.Google Scholar
  79. Trzcinski, T., & Rokita, P. (2017). Predicting popularity of online videos using support vector regression. IEEE Transactions on Multimedia, 99, 1–1.Google Scholar
  80. Tseng, C. H., & Huang, T. L. (2016). Internet advertising video facilitating health communication: Narrative and emotional perspectives. Internet Research, 26(1), 236–264.Google Scholar
  81. Vazquez-Cano, E. (2013). El videoartículo: nuevo formato de divulgación en revistas científicas y su integración en MOOCs. Comunicar: Revista Científica de Comunicación y Educación, 21(41), 83–91.Google Scholar
  82. Veletsianos, G., & Kimmons, R. (2016). Scholars in an increasingly open and digital world: How do education professors and students use twitter? The Internet and Higher Education, 30, 1–10.Google Scholar
  83. Waldrop, M. (2013). Campus 2.0. Nature, 495(7440), 160–163.Google Scholar
  84. Welbourne, D. J., & Grant, W. J. (2016). Science communication on YouTube: Factors that affect channel and video popularity. Public Understanding of Science, 25(6), 706–718.Google Scholar
  85. Xiao, C., Xue, Y., Li, Z., Luo, X., & Qin, Z. (2015). Measuring user influence based on multiple metrics on YouTube. Algorithms and Programming (PAAP), 2015 Seventh International Symposium on Parallel Architectures, 177–182.Google Scholar
  86. Zhou, R., Khemmarat, S., Gao, L., Wan, J., & Zhang, J. (2016). How YouTube videos are discovered and its impact on video views. Multimedia Tools and Applications, 75(10), 6035–6058.Google Scholar

Copyright information

© Institute of Applied Informatics at University of Leipzig 2018

Authors and Affiliations

  1. 1.UCAM Universidad Católica San Antonio de MurciaMurciaSpain
  2. 2.Airbus Helicopters EspañaToulouseSpain

Personalised recommendations