  Statistical linguistics has advanced considerably in recent decades as data
has become available. This has allowed researchers to study how statistical
properties of languages change over time. In this work, we use data from
Twitter to explore English and Spanish considering the rank diversity at
different scales: temporal (from 3 to 96 hour intervals), spatial (from 3km to
3000+km radii), and grammatical (from monograms to pentagrams). We find that
all three scales are relevant. However, the greatest changes come from
variations in the grammatical scale. At the lowest grammatical scale
(monograms), the rank diversity curves are most similar, independently on the
values of other scales, languages, and countries. As the grammatical scale
grows, the rank diversity curves vary more depending on the temporal and
spatial scales, as well as on the language and country. We also study the
statistics of Twitter-specific tokens: emojis, hashtags, and user mentions.
These particular type of tokens show a sigmoid kind of behaviour as a rank
diversity function. Our results are helpful to quantify aspects of language
statistics that seem universal and what may lead to variations.
