Affiliations: [a] Centro de Investigación en Sociedad Tecnológica y Futuro Humano, Facultad de Humanidades, Universidad Mayor, Av. Portugal N∘351, Santiago, Chile | [b] Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes. Monseñor Álvaro del Portillo 12455, Las Condes, Santiago, Chile | [c] Generation Research. Lasarettsgatan 13, 89133 Örnsköldsvik, Sweden
Correspondence:
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Corresponding author: Sebastián Maldonado, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes. Monseñor Álvaro del Portillo 12455, Las Condes, Santiago, Chile. Tel./Fax: +56 226181874; Email: smaldonado@uandes.cl.
Abstract: In this work, a data mining framework is proposed to improve the understanding of how people allocate their time. Using a multivariate approach, we performed a clustering procedure, and subsequently a regression analysis to detect which variables influence individual time use for each cluster found. Results suggest that the impact of various sociodemographic variables on sleep and work depends significantly on the characteristics of the individuals analyzed. This suggests that inquiries into time allocation and individual behavior should no longer be limited to discussions focused only on single variables. Based on our results, we recommend that researchers advance their methodological analysis towards a multifactorial approach and include clustering as a fundamental step. Proper identification of the most significant variables involved in time allocation decisions would allow researchers to better analyze and interpret their data and results.
Keywords: Time use, sleep, work, clustering, data mining
