This research evidences the usefulness of open big data to map mobility patterns in a medium-sized city. Motivated by the novel analysis that big data allow worldwide and in large metropolitan areas, we developed a methodology aiming to complement origin-destination surveys with à la carte spatial boundaries and updated data at a minimum cost. This paper validates the use of Twitter data to map the impact of public spaces on the different parts of the metropolitan area of Concepción, Chile. Results have been validated by local experts and evidence the main mobility patterns towards spaces of social interaction like malls, leisure areas, parks and so on. The map represents the mobility patterns from census districts to different categories of public spaces with schematic lines at the metropolitan scale and it is centred in the city of Concepción (Chile) and its surroundings (~10 kilometres).