Using human evaluation of 100,000 words spread across 24 corpora in 10
languages diverse in origin and culture, we present evidence of a deep imprint
of human sociality in language, observing that (1) the words of natural human
language possess a universal positivity bias; (2) the estimated emotional
content of words is consistent between languages under translation; and (3)
this positivity bias is strongly independent of frequency of word usage.
Alongside these general regularities, we describe inter-language variations in
the emotional spectrum of languages which allow us to rank corpora. We also
show how our word evaluations can be used to construct physical-like
instruments for both real-time and offline measurement of the emotional content
of large-scale texts.