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Human language reveals a universal positivity bias
Journal article   Open access   Peer reviewed

Human language reveals a universal positivity bias

Peter Sheridan Dodds, Eric M. Clark, Suma Desu, Morgan R. Frank, Andrew J. Reagan, Jake Ryland Williams, Lewis Mitchell, Kameron Decker Harris, Isabel M. Kloumann, James P. Bagrow, …
Proceedings of the National Academy of Sciences - PNAS, v 112(8), pp 2389-2394
24 Feb 2015
PMID: 25675475
url
https://doi.org/10.1073/pnas.1411678112View
Published, Version of Record (VoR) Open

Abstract

Multidisciplinary Sciences Science & Technology Science & Technology - Other Topics
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.

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