Authors:
Fernanda M. Gomes
;
Julio Neves
;
Luis Enrique Zárate Gálvez
and
Mark Song
Affiliation:
Instituto de Ciências Exatas e Informática, Pontifícia Universidade Católica de Minas Gerais, Brazil
Keyword(s):
Formal Concept Analysis, Mental Health, Social Media, Sleep Quality, Data Science, Lattice Miner, Loneliness.
Abstract:
Social media platforms have reshaped personal interactions, allowing engagement with diverse audiences. However, growing evidence suggests that these platforms may also contribute to mental health challenges. This paper investigates the associations between social media usage patterns, loneliness, and sleep quality, using Formal Concept Analysis (FCA) on data from a sample in Bangladesh. The dataset includes information on social media habits, loneliness, anxiety, depression, and sleep disturbances, using metrics from validated psychological scales. Through FCA, this study extracted implication rules that describe how specific social media usage behaviors relate to feelings of loneliness and sleep issues. Findings show that individuals with high levels of social media engagement report shorter sleep durations and heightened symptoms of loneliness. FCA is used in this study to uncover non-obvious relationships within complex datasets, making it a valuable approach for analyzing patter
ns between social media behaviors and mental health outcomes.
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