  Despite their relatively low sampling factor, the freely available, randomly
sampled status streams of Twitter are very useful sources of geographically
embedded social network data. To statistically analyze the information Twitter
provides via these streams, we have collected a year's worth of data and built
a multi-terabyte relational database from it. The database is designed for fast
data loading and to support a wide range of studies focusing on the statistics
and geographic features of social networks, as well as on the linguistic
analysis of tweets. In this paper we present the method of data collection, the
database design, the data loading procedure and special treatment of geo-tagged
and multi-lingual data. We also provide some SQL recipes for computing network
statistics.
