Human language reveals a universal positivity bias

Human language reveals a universal positivity bias

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 emotion...

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Bibliographic Details
Main Authors: 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
Other Authors: Massachusetts Institute of Technology. Center for Computational Engineering
Format: Article
Language:en_US
Published: National Academy of Sciences (U.S.) 2015
Online Access:http://hdl.handle.net/1721.1/98030
https://orcid.org/0000-0001-9487-9359
Description
Summary: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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