Human language reveals a universal positivity bias
Author(s)Dodds, Peter Sheridan; Clark, Eric M.; Desu, Suma; Reagan, Andrew J.; Williams, Jake Ryland; Mitchell, Lewis; Harris, Kameron Decker; Kloumann, Isabel M.; Bagrow, James P.; Megerdoomian, Karine; McMahon, Matthew T.; Tivnan, Brian F.; Danforth, Christopher M.; Frank, Morgan Ryan; ... Show more Show less
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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.
DepartmentMassachusetts Institute of Technology. Center for Computational Engineering; Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Proceedings of the National Academy of Sciences
National Academy of Sciences (U.S.)
Dodds, Peter Sheridan, Eric M. Clark, Suma Desu, Morgan R. Frank, Andrew J. Reagan, Jake Ryland Williams, Lewis Mitchell, et al. “Human Language Reveals a Universal Positivity Bias.” Proc Natl Acad Sci USA 112, no. 8 (February 9, 2015): 2389–2394.
Final published version