  Because of its willingness to share data with academia and industry, Twitter
has been the primary social media platform for scientific research as well as
for consulting businesses and governments in the last decade. In recent years,
a series of publications have studied and criticized Twitter's APIs and Twitter
has partially adapted its existing data streams. The newest Twitter API for
Academic Research allows to "access Twitter's real-time and historical public
data with additional features and functionality that support collecting more
precise, complete, and unbiased datasets." The main new feature of this API is
the possibility of accessing the full archive of all historic Tweets. In this
article, we will take a closer look at the Academic API and will try to answer
two questions. First, are the datasets collected with the Academic API
complete? Secondly, since Twitter's Academic API delivers historic Tweets as
represented on Twitter at the time of data collection, we need to understand
how much data is lost over time due to Tweet and account removal from the
platform. Our work shows evidence that Twitter's Academic API can indeed create
(almost) complete samples of Twitter data based on a wide variety of search
terms. We also provide evidence that Twitter's data endpoint v2 delivers better
samples than the previously used endpoint v1.1. Furthermore, collecting Tweets
with the Academic API at the time of studying a phenomenon rather than creating
local archives of stored Tweets, allows for a straightforward way of following
Twitter's developer agreement. Finally, we will also discuss technical
artifacts and implications of the Academic API. We hope that our work can add
another layer of understanding of Twitter data collections leading to more
reliable studies of human behavior via social media data.
