  Large scale analysis and statistics of socio-technical systems that just a
few short years ago would have required the use of consistent economic and
human resources can nowadays be conveniently performed by mining the enormous
amount of digital data produced by human activities. Although a
characterization of several aspects of our societies is emerging from the data
revolution, a number of questions concerning the reliability and the biases
inherent to the big data "proxies" of social life are still open. Here, we
survey worldwide linguistic indicators and trends through the analysis of a
large-scale dataset of microblogging posts. We show that available data allow
for the study of language geography at scales ranging from country-level
aggregation to specific city neighborhoods. The high resolution and coverage of
the data allows us to investigate different indicators such as the linguistic
homogeneity of different countries, the touristic seasonal patterns within
countries and the geographical distribution of different languages in
multilingual regions. This work highlights the potential of geolocalized
studies of open data sources to improve current analysis and develop indicators
for major social phenomena in specific communities.
