  Lifestyles are a valuable model for understanding individuals' physical and
mental lives, comparing social groups, and making recommendations for improving
people's lives. In this paper, we examine and compare lifestyle behaviors of
people living in cities of different sizes, utilizing freely available social
media data as a large-scale, low-cost alternative to traditional survey
methods. We use the Greater New York City area as a representative for large
cities, and the Greater Rochester area as a representative for smaller cities
in the United States. We employed matrix factor analysis as an unsupervised
method to extract salient mobility and work-rest patterns for a large
population of users within each metropolitan area. We discovered interesting
human behavior patterns at both a larger scale and a finer granularity than is
present in previous literature, some of which allow us to quantitatively
compare the behaviors of individuals of living in big cities to those living in
small cities. We believe that our social media-based approach to lifestyle
analysis represents a powerful tool for social computing in the big data age.
