Before revision:  Despite sampling rates having clear temporal variations, we find that the Bernoulli process with a uniform rate well approximates Twitter data sampling, and it allows to estimate the ground-truth entity frequency and ranking with the observed sample data.
After revision:  Sampling also differs significantly across timescales. While the hourly sampling rate is influenced by the diurnal rhythm in different time zones, the millisecond level sampling is heavily affected by the implementation choices. For Twitter entities such as users, we find the Bernoulli process with a uniform rate well approximates Twitter data sampling, and it allows to estimate the ground-truth entity frequency and ranking with the observed sample data.