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Using Data Mining to Discover New Patterns of Social Media and Smartphone Use and Emotional States

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posted on 2024-05-29, 02:04 authored by Yeslam Al-Saggaf, Md Anisur RahmanMd Anisur Rahman, Uffe Kock Wiil
Social media and smartphone use are strongly linked to users' emotional states. While numerous studies have established that fear of missing out (FOMO), boredom, and loneliness predict social media and smartphone use, numerous other studies have concluded that social media and smartphone use negatively impact these emotional states (i.e., FOMO, boredom, and loneliness). Phubbing (phone snubbing), which is the act of ignoring a physically present person in favour of a smartphone, is associated with both social media and smartphone use and users’ emotional states. Much of the above research, however, has adopted the traditional hypothesis testing method. So far, limited work has been done using data-driven approaches. This paper uses data mining techniques to uncover previously unknown patterns about social media and smartphone use, phubbing, and users' emotional states based on two existing datasets originating from online questionnaires facilitated through social media. Novel patterns related to FOMO, loneliness, boredom, and phubbing are discovered and explored in detail. The study also demonstrates the usefulness of the data-driven approach and establishes it as a valid alternative to the hypothesis-driven approach to investigating social media and smartphone use, phubbing, and users' emotional states.


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Social Network Analysis and Mining



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Springer Nature



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© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit

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