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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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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.
Date issued
2015-02
URI
http://hdl.handle.net/1721.1/98030
Department
Massachusetts Institute of Technology. Center for Computational Engineering; Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
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.
Version: Final published version
ISSN
0027-8424
1091-6490

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