Surfing the Social Networks

  • Cristóbal Fernández RobinEmail author
  • Scott McCoy
  • Diego Yáñez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9742)


This research aims to determine why people use Social Networks using an adaptation of the UTAUT2 model. The proposed model considers Subjective Norm, Perceived Playfulness, Perceived Ease of Use, and Perceived Usefulness as predictors of the Intention to Use. Five social networks were chosen in order to carry out this research: Facebook, Twitter, Instagram, WhatsApp, and LinkedIn. Findings shows that social networks are more useful to serve his or her purposes when more people close to the individual are using them. Perceived Playfulness proves to be a strong predictor of Intention to Use Facebook, Instagram, and WhatsApp, all these social networks are used for leisure purposes. Perceived Usefulness proves to be the most powerful predictor for Intention to Use in LinkedIn, this social network is mainly used for work purposes. Finally, both Perceived Playfulness and Perceived Usefulness are good predictors of Intention to Use Twitter. Implications are discussed.


Social Network Internet Intention to Use 


  1. Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)CrossRefGoogle Scholar
  2. Brandtzæg, P.B., Heim, J.: Why people use social networking sites. In: Ozok, A.A., Panayiotis, Z. (eds.) Online Communities and Social Computing. LNCS, vol. 5621, pp. 143–152. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. Chen, Y.F.: See you on Facebook: exploring influences on Facebook continuous usage. Behav. Inf. Technol. 33(11), 1208–1218 (2014)CrossRefGoogle Scholar
  4. Cheong, J., Park, M.C.: Mobile internet acceptance in Korea. Internet Res. 15(2), 125–140 (2005)CrossRefGoogle Scholar
  5. Cheung, T.T.: A study on motives, usage, self-presentation and number of followers on instagram (2014)Google Scholar
  6. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989)CrossRefGoogle Scholar
  7. Ellison, N.B., Steinfield, C., Lampe, C.: The benefits of Facebook “friends:” social capital and college students’ use of online social network sites. J. Comput.-Mediated Commun. 12(4), 1143–1168 (2007)CrossRefGoogle Scholar
  8. Java, A., Song, X., Finin, T., Tseng, B.: Why we Twitter: understanding microblogging usage and communities. In: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web Mining and Social Network Analysis, pp. 56–65. ACM, August 2007Google Scholar
  9. Li, D.C.: Online social network acceptance: a social perspective. Internet Res. 21(5), 562–580 (2011)CrossRefGoogle Scholar
  10. Moon, J.W., Kim, Y.G.: Extending the TAM for a world-wide-web context. Inf. Manag. 38(4), 217–230 (2001)CrossRefGoogle Scholar
  11. Narula, S., Jindal, N.: Use of social network sites by AUMP students: a comparative study on Facebook, Twitter and Instagram usage. J. Adv. Res. Journalism Mass Commun. 2(2), 20–24 (2015)Google Scholar
  12. Park, E., Ohm, J.: Factors influencing users’ employment of mobile map services. Telematics Inform. 31(2), 253–265 (2014)CrossRefGoogle Scholar
  13. Pelling, E.L., White, K.M.: The theory of planned behavior applied to young people’s use of social networking web sites. CyberPsychol. Behav. 12(6), 755–759 (2009)CrossRefGoogle Scholar
  14. Schneider, F., Feldmann, A., Krishnamurthy, B., Willinger, W.: Understanding online social network usage from a network perspective. In: Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference, pp. 35–48. ACM, November 2009Google Scholar
  15. Sledgianowski, D., Kulviwat, S.: Using social network sites: the effects of playfulness, critical mass and trust in a hedonic context. J. Comput. Inf. Syst. 49(4), 74 (2009)Google Scholar
  16. Smith, C.: DMR (n.d.). Accessed 15 Oct 2015
  17. Shin, D.H., Shin, Y.J., Choo, H., Beom, K.: Smartphones as smart pedagogical tools: implications for smartphones as u-learning devices. Comput. Hum. Behav. 27(6), 2207–2214 (2011)CrossRefGoogle Scholar
  18. Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  19. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478 (2003)Google Scholar
  20. Venkatesh, V., Thong, J.Y., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36(1), 157–178 (2012)Google Scholar
  21. Xu, C., Ryan, S., Prybutok, V., Wen, C.: It is not for fun: an examination of social network site usage. Inf. Manag. 49(5), 210–217 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Cristóbal Fernández Robin
    • 1
    Email author
  • Scott McCoy
    • 2
  • Diego Yáñez
    • 1
  1. 1.Universidad Técnica Federico Santa MaríaValparaísoChile
  2. 2.Mason School of BusinessWilliamsburgUSA

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