I'm not sure what to make of the data presented in this study of the frequency of emotion words in books, but it's intriguing.

We also found a general decrease in emotional word usage in the past decades up to the present, which was observed also in fiction writing on its own. We interpret this as a genuine decrease in the literary expression of emotion, but an alternative explanation could be that mood words have changed, rather than decreased in usage, through the century. This seems unlikely to explain the observed decrease, however, because we used contemporary word lists, analyzed recently in Twitter data to characterize recent events [24], any bias of which should have increased in usage towards the present.

Our results also support the popular notion that American authors express more emotion than the British. Somewhat surprisingly, this difference has apparently developed only since the 1960s, and as part of a more general stylistic differentiation in American versus British English, reflected similarly in content-free word frequencies. This relative increase of American mood word use roughly coincides with the increase of anti–social and narcissistic sentiments in U.S. popular song lyrics from 1980 to 2007 [6], as evidenced by steady increases in angry/antisocial lyrics and in the percentage of first-person singular pronouns (e.g., I, me,mine), with a corresponding decrease in words indicating social interactions (e.g., mate, talk,child) over the same 27-year period [6].

As these findings appear to genuinely reflect changes in published language, a remaining question is whether word usage represents real behavior in a population, or possibly an absence of that behavior which is increasingly played out via literary fiction (or online discourse).

The joy-sadness curve, in particular, caught my eye. World War II seemed to cause a big spike in sadness, and the early 80's were a rough time too, though I have no idea why.

I wonder if the n-gram data from Google will include stickers and emoji for future generations to analyze.