Abstract
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.
This is a preview of subscription content, log in via an institution.
Notes
- 1.
See http://trams.disi.unitn.it for more information.
References
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)
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)
Boase, J., Ling, R.: Measuring mobile phone use: self-report versus log data. J. Comput. Mediated Commun. 18(4), 508–519 (2013)
Eagle, N., Pentland, A.S.: Reality mining: sensing complex social systems. Pers. Ubiquit. Comput. 10(4), 255–268 (2006)
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)
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)
Hellgren, M.: Extracting more knowledge from time diaries? Soc. Indic. Res. 119(3), 1517–1534 (2014)
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)
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)
Juster, F.T., Stafford, F.P.: Time, Goods, and Well-being. University of Michigan (1985)
Kan, M.Y., Pudney, S.: Measurement error in stylized and diary data on time use. Sociol. Methodol. 38(1), 101–132 (2008)
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)
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)
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)
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). 2158244015573169
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)
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)
Romano., M.: Time use in daily life. a multidisciplinary approach to the time use’s analysis. Technical report ISTAT No 35 (2008)
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)
Samaha, M., Hawi, N.S.: Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Comput. Hum. Behav. 57, 321–325 (2016)
Shelley, K.J.: Developing the american time use survey activity classification system. Monthly Lab. Rev. 128, 3 (2005)
Sorokin, P.A., Berger, C.Q.: Time-Budgets of Human Behavior, vol. 2. Harvard University Press, Cambridge (1939)
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)
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)
Acknowledgments
This work has been supported by QROWD (http://qrowd-project.eu/), a Horizon 2020 project, under Grant Agreement N\(^{\circ }\) 732194.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Giunchiglia, F., Zeni, M., Gobbi, E., Bignotti, E., Bison, I. (2017). Mobile Social Media and Academic Performance. In: Ciampaglia, G., Mashhadi, A., Yasseri, T. (eds) Social Informatics. SocInfo 2017. Lecture Notes in Computer Science(), vol 10540. Springer, Cham. https://doi.org/10.1007/978-3-319-67256-4_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-67256-4_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67255-7
Online ISBN: 978-3-319-67256-4
eBook Packages: Computer ScienceComputer Science (R0)