How do you compare term counts between two different periods, with different underlying corpus sizes, without bias?
The approach suggested by j.a.gartner is good if you want to analyze the quarter-to-quarter change in frequency for a given term, considering only that term in isolation.  What it doesn't do is evaluate the relative frequency compared to all other terms in the corpus.  For this you could compare frequency rank for all terms quarter-to-quarter. This is the analysis used in Zipf's Law.  Another advantage of this analysis is that you can test whether the generating process is or is not stationary (e.g. governed by same distribution quarter to quarter).

The advantage of comparing frequency rank is that it doesn't depend on the relative size of the corpus for each quarter (as long as they are all "large").  In simple language, the frequency rank of the word "Christmas" in the 4th quarter will probably be the same, regardless of whether the (US English news) corpus is 10,000 articles or 1,000,000 articles.