Los sistemas de recomendación online en el mercado audiovisual español: análisis comparativo entre Atresmedia, Movistar +, y Netflix

  1. Mónica Herrero Subías 1
  2. Mercedes Medina Laverón 1
  3. Alicia María Urgellés Molina 2
  1. 1 Universidad de Navarra
    info

    Universidad de Navarra

    Pamplona, España

    ROR https://ror.org/02rxc7m23

  2. 2 Universidad de los Hemisferios
    info

    Universidad de los Hemisferios

    Quito, Ecuador

    ROR https://ror.org/02sqp5835

Zeitschrift:
UCJC Business & Society Review

ISSN: 2659-3270

Datum der Publikation: 2018

Nummer: 60

Seiten: 54-89

Art: Artikel

DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Andere Publikationen in: UCJC Business & Society Review

Zusammenfassung

El objetivo principal de este artículo es estudiar el valor que diferentes servicios audiovisuales online conceden a los sistemas de recomendaciones. Analizamos tres servicios que operan actualmente en España: Atresmedia, Movistar + y Netflix. Se propone un conjunto de criterios para comparar las recomendaciones presentes en cada plataforma y el uso que las empresas hacen de ellas. Los resultados muestran que los servicios audiovisuales han implementado las recomendaciones en diferente medida de acuerdo con su modelo de negocio y su actividad principal.

Bibliographische Referenzen

  • Alba, D. (2017, January). Netflix is killing it -big timeafter pouring cash into original shows. Wired.com. Retrieved from http:.//www.wired.com.
  • Ajzen, I. & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Englewood Cliffs, NJ: Prentice-Hall.
  • Anderson, S. P., Foros, Ø., & Kind, H. J. (2018). Competition for advertisers and for viewers in media markets. The Economic Journal, 128(608), 34-54.
  • Ang, I. (1991). Desperately seeking the audience. London: Routledge. Carr, D. (2013, February). Giving Viewers What They Want. The New York Times. Retrieved from http://www.nytimes.com.
  • CNMC (2016). Informe Económico Sectorial de las Telecomunicaciones y el Audiovisual, Madrid: CNMC, Retrieved from CNMC website: http://data.cnmc.es/datagraph/files/ Informe%20Telecos%20y%20Audiovisual%202016.pdf (accessed 20 July 2017).
  • Cohn, J. (2016). My TiVo Thinks I’m Gay: Algorithmic Culture and Its Discon. Television & New Media, 17(8), 675–690.
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
  • Gillespie, T. (2014). The relevance of algorithms. Retrieved October 13, 2017, from https:// ebookcentral.proquest.com/lib/oxford/reader.action?docID=3339732.
  • Gillespie, T. (2017). Algorithmically recognizable: Santorum’s Google problem, and Google’s Santorum problem. Information, Communication & Society, 20(1), 63–80.
  • Gomez-Uribe, C. A., & Hunt, N. (2015). The Netflix Recommender System. ACM Transactions on Management Information Systems, 6(4), 1–19.
  • Hallinan, B. & Striphas, T. (2016). Recommended for you: The Netflix Prize and the production of algorithmic culture. New Media & Society 18 (1), 117-137.
  • Helberger, N., Karpinnen, K., & D’Acunto, L. (2018). Exposure diversity as a design principle for recommender systems. Information, Communication & Society, 21(2), 191–207.
  • Kitchin, R. (2017). The social power of algorithms. Information, Communication & Society, 20(1), 1–13. Lago, Santiago (2017, January). Movistar. No queremos ser comparados con Netflix y HBO. Hipertextual. Retrieved from: https://hipertextual.com/2017/01/movistar-hbo-netflix.
  • Leber, J. (2013, February). “House of Cards” and Our Future of Algorithmic Programming. MIT Technology Review. Retrieved from: https://www.technologyreview.com/s/511771/ house-of-cards-and-our-future-of-algorithmic-programming.
  • Leeker, M., Shipper, I., & Beyes, T. (2017). Perfoming the Digital. Bielefeld: Digital Society. Lekakos, G., Charami, M., & Caravelas, P. (2009). Personalized Movie Recommendation. In B. Furht (Ed.), Handbook of Multimedia for Digital Entertainment and Arts (pp. 3–26).
  • Boston: Springer. Marcos, N. (2016). Netflix, HBO o Movistar. Comparamos catálogos, precios y características técnicas de las plataformas de televisión a la carta. El País, Available from: http://cultura.elpais.com/cultura/2016/12/03/television/1480762612_522890.html (accessed 7 December 2016).
  • Medina, M., Herrero, M., & and Etayo, C. (2015). The impact of digitalization on the strategies of pay TV in Spain, Revista Latina de Comunicación Social, 70, 252-269.
  • Morris, J. W. (2015). Curation by code: Infomediaries and the data mining of taste. European Journal of Cultural Studies, 18(45), 446–463.
  • Napoli, P. M. (2014). Automated Media: An Institutional Theory Perspective on Algorithmic Media Production and Consumption. Communication Theory, 24(3), 340–360.
  • Netflix (2016a). Cronología de Netflix. Available from: https://media.netflix.com/es/aboutnetflix (accessed 3 March 2017).
  • Netflix (2016b). Netflix Is Now Available Around the World. Netflix Media Centre. Available from: https://media.netflix.com/en/press-releases/netflix-is-now-available-around-the-world (accessed 6 January 2016).
  • Newman, N., Fletcher, R., Levy, D., & Nielsen, R. K. (2016). Reuters Institute Digital News Report 2016. Oxford: Reuters Institute for the Study of Journalism. Available from: http:// reutersinstitute.politics.ox.ac.uk/sites/default/files/research/files/Digital%2520News%2520R eport%25202016.pdf.
  • Portilla, I. (2015). Television Audience Measurement: Proposals of the Industry in the Era of Digitalization. Trípodos, 36, 75-92.
  • Striphas, T. (2015). Algorithmic culture. European Journal of Cultural Studies, 18(45), 395–412.
  • Telefónica (2016) La Sociedad de la Información en España 2016. Madrid: Fundación Telefónica Ariel. Available from: http://www.fundaciontelefonica.com/arte_cultura/sociedadde-la-informacion/informe-sie-espana-2016/.
  • Tryon, C. (2015). TV got better: Netflix’s original programming strategies and binge viewing. Media Industries Journal 2.2, 2(2), 104–116.
  • Turow, J. (2005). Audience Construction and Culture Production: Marketing Surveillance in the Digital Age. The ANNALS of the American Academy of Political and Social Science, 597(1), 103–121.
  • Van Den Bulck, H., & Moe, H. (2017). Public service media, universality and personalisation through algorithms: mapping strategies and exploring dilemmas. Media, Culture and Society, 40(60), 1–18.
  • Willson, M. (2017). Algorithms (and the) everyday. Information, Communication & Society, 20(1), 137–150.
Fuente de los datos: Dialnet