  Social network data offer interesting opportunities in urban studies. In this
study, we used Twitter data to analyse city dynamics over the course of the
day. Users of this social network were grouped according to city zone and time
slot in order to analyse the daily dynamics of the city and the relationship
between this and land use. First, daytime activity in each zone was compared
with activity at night in order to determine which zones showed increased
activity in each of the time slots. Then, typical Twitter activity profiles
were obtained based on the predominant land use in each zone, indicating how
land uses linked to activities were activated during the day, but at different
rates depending on the type of land use. Lastly, a multiple regression analysis
was performed to determine the influence of the different land uses on each of
the major time slots (morning, afternoon, evening and night) through their
changing coefficients. Activity tended to decrease throughout the day for most
land uses (e.g. offices, education, health and transport), but remained
constant in parks and increased in retail and residential zones. Our results
show that social network data can be used to improve our understanding of the
link between land use and urban dynamics.
