  This paper maps the large-scale variation of the Spanish language by
employing a corpus based on geographically tagged Twitter messages. Lexical
dialects are extracted from an analysis of variants of tens of concepts. The
resulting maps show linguistic variation on an unprecedented scale across the
globe. We discuss the properties of the main dialects within a machine learning
approach and find that varieties spoken in urban areas have an international
character in contrast to country areas where dialects show a more regional
uniformity.
