  It is tempting to treat frequency trends from the Google Books data sets as
indicators of the "true" popularity of various words and phrases. Doing so
allows us to draw quantitatively strong conclusions about the evolution of
cultural perception of a given topic, such as time or gender. However, the
Google Books corpus suffers from a number of limitations which make it an
obscure mask of cultural popularity. A primary issue is that the corpus is in
effect a library, containing one of each book. A single, prolific author is
thereby able to noticeably insert new phrases into the Google Books lexicon,
whether the author is widely read or not. With this understood, the Google
Books corpus remains an important data set to be considered more lexicon-like
than text-like. Here, we show that a distinct problematic feature arises from
the inclusion of scientific texts, which have become an increasingly
substantive portion of the corpus throughout the 1900s. The result is a surge
of phrases typical to academic articles but less common in general, such as
references to time in the form of citations. We highlight these dynamics by
examining and comparing major contributions to the statistical divergence of
English data sets between decades in the period 1800--2000. We find that only
the English Fiction data set from the second version of the corpus is not
heavily affected by professional texts, in clear contrast to the first version
of the fiction data set and both unfiltered English data sets. Our findings
emphasize the need to fully characterize the dynamics of the Google Books
corpus before using these data sets to draw broad conclusions about cultural
and linguistic evolution.
