Abstract
This research aimed, firstly, to define a conceptual model that considers potential resources/challenges (Physical, Cognitive, Emotional, Social, Material, Environmental, Digital) and describes how those influence the Internet use and modify human behavior during life transitions (e.g., changing school, finding a job). Secondly, starting on that model, user profiles were outlined. Instead of grouping study participants into pre-defined groups, clustering techniques were used to group users with similar profiles. The main advantage of this methodological approach is that the participant groups, i.e., different user profiles, emerged intrinsically from the data. A cross-sectional study was proposed based on the compilation of an Online questionnaire. The sample consists of 1.524 participants. Three clusters emerged with different mean ages: young adult users (mean age = 33.83), youngest users (25.79), and oldest users (36.80). Differences were identified between all dimensions measured, particularly between youngest users and oldest users.
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Acknowledgments
Thanks to Jeffrey Earp for language revision of the original manuscript. This study has been funded by national funds, through FCT, Portuguese Science Foundation, under project UIDB/05037/2020.
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Benvenuti, M., Rocha, H., Dimas, I.D., Mazzoni, E. (2022). How Life Transitions Influence People’s Use of the Internet: A Clustering Approach. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13378. Springer, Cham. https://doi.org/10.1007/978-3-031-10562-3_8
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