  We observe and report on a systematic relationship between population density
and Twitter use. Number of tweets, number of users and population per unit area
are related by power laws, with exponents greater than one, that are consistent
with each other and across a range of spatial scales. This implies that
population density can accurately predict Twitter activity. Furthermore this
trend can be used to identify `anomalous' areas that deviate from the trend.
Analysis of geo-tagged and place-tagged tweets show that geo-tagged tweets are
different with respect to user type and content. Our findings have implications
for the spatial analysis of Twitter data and for understanding demographic
biases in the Twitter user base.
