Mobile Social Media and Academic Performance

  • Fausto GiunchigliaEmail author
  • Mattia ZeniEmail author
  • Elisa Gobbi
  • Enrico BignottiEmail author
  • Ivano Bison
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10540)


Recent studies have shown that there is a negative correlation between social media and academic performance, since they can lead to behaviours that hurt students’ careers, e.g., addictedness. However, these studies either focus on smartphones and social media addictedness per se or rely on sociological surveys, which only provide approximate estimations of the phenomena. We propose to bridge this gap by (i) parametrizing social media usage and academic performance and (ii) combining smartphones and time diaries to keep track of users’ activities and their smartphone interaction. By analyzing the logs of social media apps while studying and attending lessons, and comparing them to students’ GPA, we can quantify negative and positive correlations via smartphones.


Social media Academic performance Smartphones Time diaries 



This work has been supported by QROWD (, a Horizon 2020 project, under Grant Agreement N\(^{\circ }\) 732194.


  1. 1.
    Al-Barashdi, H.S., Bouazza, A., Jabur, N.H.: Smartphone addiction among university undergraduates: a literature review. J. Sci. Res. Rep. 4(3), 210–225 (2015)Google Scholar
  2. 2.
    Andrews, S., Ellis, D.A., Shaw, H., Piwek, L.: Beyond self-report: tools to compare estimated and real-world smartphone use. PLoS ONE 10(10), e0139004 (2015)CrossRefGoogle Scholar
  3. 3.
    Boase, J., Ling, R.: Measuring mobile phone use: self-report versus log data. J. Comput. Mediated Commun. 18(4), 508–519 (2013)CrossRefGoogle Scholar
  4. 4.
    Eagle, N., Pentland, A.S.: Reality mining: sensing complex social systems. Pers. Ubiquit. Comput. 10(4), 255–268 (2006)CrossRefGoogle Scholar
  5. 5.
    Giunchiglia, F., Bignotti, E., Zeni, M.: Personal context modelling and annotation. In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 117–122. IEEE (2017)Google Scholar
  6. 6.
    Gökçearslan, Ş., Mumcu, F.K., Haşlaman, T., Çevik, Y.D.: Modelling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students. Comput. Hum. Behav. 63, 639–649 (2016)CrossRefGoogle Scholar
  7. 7.
    Hellgren, M.: Extracting more knowledge from time diaries? Soc. Indic. Res. 119(3), 1517–1534 (2014)CrossRefGoogle Scholar
  8. 8.
    Jeong, S.H., Kim, H., Yum, J.Y., Hwang, Y.: What type of content are smartphone users addicted to? SNS vs. games. Comput. Hum. Behav. 54, 10–17 (2016)CrossRefGoogle Scholar
  9. 9.
    Junco, R.: Too much face and not enough books: the relationship between multiple indices of facebook use and academic performance. Comput. Hum. Behav. 28(1), 187–198 (2012)CrossRefGoogle Scholar
  10. 10.
    Juster, F.T., Stafford, F.P.: Time, Goods, and Well-being. University of Michigan (1985)Google Scholar
  11. 11.
    Kan, M.Y., Pudney, S.: Measurement error in stylized and diary data on time use. Sociol. Methodol. 38(1), 101–132 (2008)CrossRefGoogle Scholar
  12. 12.
    Kwon, M., Lee, J.Y., Won, W.Y., Park, J.W., Min, J.A., Hahn, C., Gu, X., Choi, J.H., Kim, D.J.: Development and validation of a smartphone addiction scale (sas). PLoS ONE 8(2), e56936 (2013)CrossRefGoogle Scholar
  13. 13.
    Lee, H., Ahn, H., Nguyen, T.G., Choi, S.W., Kim, D.J.: Comparing the self-report and measured smartphone usage of college students: a pilot study. Psychiatry invest. 14(2), 198–204 (2017)CrossRefGoogle Scholar
  14. 14.
    Lee, U., Lee, J., Ko, M., Lee, C., Kim, Y., Yang, S., Yatani, K., Gweon, G., Chung, K.M., Song, J.: Hooked on smartphones: an exploratory study on smartphone overuse among college students. In: Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems, pp. 2327–2336. ACM (2014)Google Scholar
  15. 15.
    Lepp, A., Barkley, J.E., Karpinski, A.C.: The relationship between cell phone use and academic performance in a sample of us college students. Sage Open 5(1), 1–9 (2015). 2158244015573169CrossRefGoogle Scholar
  16. 16.
    Meier, A., Reinecke, L., Meltzer, C.E.: “Facebocrastination”? predictors of using facebook for procrastination and its effects on students well-being. Comput. Hum. Behav. 64, 65–76 (2016)CrossRefGoogle Scholar
  17. 17.
    Paul, J.A., Baker, H.M., Cochran, J.D.: Effect of online social networking on student academic performance. Comput. Hum. Behav. 28(6), 2117–2127 (2012)CrossRefGoogle Scholar
  18. 18.
    Romano., M.: Time use in daily life. a multidisciplinary approach to the time use’s analysis. Technical report ISTAT No 35 (2008)Google Scholar
  19. 19.
    Rosen, L.D., Carrier, L.M., Cheever, N.A.: Facebook and texting made me do it: media-induced task-switching while studying. Comput. Hum. Behav. 29(3), 948–958 (2013)CrossRefGoogle Scholar
  20. 20.
    Samaha, M., Hawi, N.S.: Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Comput. Hum. Behav. 57, 321–325 (2016)CrossRefGoogle Scholar
  21. 21.
    Shelley, K.J.: Developing the american time use survey activity classification system. Monthly Lab. Rev. 128, 3 (2005)Google Scholar
  22. 22.
    Sorokin, P.A., Berger, C.Q.: Time-Budgets of Human Behavior, vol. 2. Harvard University Press, Cambridge (1939)Google Scholar
  23. 23.
    Wang, R., Harari, G., Hao, P., Zhou, X., Campbell, A.T.: SmartGPA: how smartphones can assess and predict academic performance of college students. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 295–306. ACM (2015)Google Scholar
  24. 24.
    Zeni, M., Zaihrayeu, I., Giunchiglia, F.: Multi-device activity logging. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication, pp. 299–302. ACM (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Information Engineering and Computer ScienceUniversity of TrentoTrentoItaly
  2. 2.Department of Sociology and Social ResearchUniversity of TrentoTrentoItaly

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