Human language reveals a universal positivity bias.

Picture of Peter Sheridan Dodds
Peter Sheridan Dodds
Picture of Eric M Clark
Eric M Clark
Picture of Suma Desu
Suma Desu
Picture of Andrew J Reagan
Andrew J Reagan
Picture of Jake Ryland Williams
Jake Ryland Williams
Picture of Lewis Mitchell
Lewis Mitchell
Picture of Kameron Decker Harris
Kameron Decker Harris
Picture of Isabel M Kloumann
Isabel M Kloumann
Picture of James P Bagrow
James P Bagrow
Picture of Karine Megerdoomian
Karine Megerdoomian
Picture of Matthew T McMahon
Matthew T McMahon
Picture of Brian F Tivnan
Brian F Tivnan
Picture of Christopher M Danforth
Christopher M Danforth
Teaser image

Abstract

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 (i) the words of natural human language possess a universal positivity bias, (ii) the estimated emotional content of words is consistent between languages under translation, and (iii) this positivity bias is strongly independent of frequency of word use. Alongside these general regularities, we describe interlanguage variations in the emotional spectrum of languages that 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.

Materials