Deciphering dynamics in time use reveals the complexity of human behavior, individually and socially. This study analyzes detailed activity logs from a demographically representative sample of more than 230,000 individuals who participated in the American Time Use Survey (ATUS) conducted annually and nationally since 2003. It applies the method proposed by (Jiang et al. 2012) to analyze the inherent daily activity structure of individuals, the variation of individual daily activities, and clusters of individual behaviors along with their socio-demographic context. Results show that Americans can be clustered into 6 and 7 representative groups according to their activities during weekdays and weekends, respectively.
The project received feedback from reviewers and attendees of the 10th International Conference on Computational Social Science, during which it was presented as a poster.
Jiang, S., Ferreira, J., & González, M. C. (2012). Clustering daily patterns of human activities in the city. Data Mining and Knowledge Discovery, 25(3), 478–510. https://doi.org/10.1007/s10618-012-0264-z