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.