Literature DB >> 25675475

Human language reveals a universal positivity bias.

Peter Sheridan Dodds1, Eric M Clark2, Suma Desu3, Morgan R Frank3, Andrew J Reagan2, Jake Ryland Williams2, Lewis Mitchell4, Kameron Decker Harris5, Isabel M Kloumann6, James P Bagrow2, Karine Megerdoomian7, Matthew T McMahon7, Brian F Tivnan8, Christopher M Danforth1.   

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.

Entities:  

Keywords:  happiness; language; positivity; social psychology

Mesh:

Year:  2015        PMID: 25675475      PMCID: PMC4345622          DOI: 10.1073/pnas.1411678112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  7 in total

1.  The secret life of pronouns: flexibility in writing style and physical health.

Authors:  R Sherlock Campbell; James W Pennebaker
Journal:  Psychol Sci       Date:  2003-01

2.  Affective biases in English are bi-dimensional.

Authors:  Amy Beth Warriner; Victor Kuperman
Journal:  Cogn Emot       Date:  2014-10-14

3.  The Effect of Language on Economic Behavior: Evidence from Savings Rates, Health Behaviors, and Retirement Assets.

Authors:  M Keith Chen
Journal:  Am Econ Rev       Date:  2013-04

4.  Quantitative analysis of culture using millions of digitized books.

Authors:  Jean-Baptiste Michel; Yuan Kui Shen; Aviva Presser Aiden; Adrian Veres; Matthew K Gray; Joseph P Pickett; Dale Hoiberg; Dan Clancy; Peter Norvig; Jon Orwant; Steven Pinker; Martin A Nowak; Erez Lieberman Aiden
Journal:  Science       Date:  2010-12-16       Impact factor: 47.728

5.  Positivity of the English language.

Authors:  Isabel M Kloumann; Christopher M Danforth; Kameron Decker Harris; Catherine A Bliss; Peter Sheridan Dodds
Journal:  PLoS One       Date:  2012-01-11       Impact factor: 3.240

6.  Temporal patterns of happiness and information in a global social network: hedonometrics and Twitter.

Authors:  Peter Sheridan Dodds; Kameron Decker Harris; Isabel M Kloumann; Catherine A Bliss; Christopher M Danforth
Journal:  PLoS One       Date:  2011-12-07       Impact factor: 3.240

7.  The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place.

Authors:  Lewis Mitchell; Morgan R Frank; Kameron Decker Harris; Peter Sheridan Dodds; Christopher M Danforth
Journal:  PLoS One       Date:  2013-05-29       Impact factor: 3.240

  7 in total
  47 in total

1.  Mining Social Media Data for Biomedical Signals and Health-Related Behavior.

Authors:  Rion Brattig Correia; Ian B Wood; Johan Bollen; Luis M Rocha
Journal:  Annu Rev Biomed Data Sci       Date:  2020-05-04

2.  The language-dependent relationship between word happiness and frequency.

Authors:  David Garcia; Antonios Garas; Frank Schweitzer
Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-21       Impact factor: 11.205

3.  Reply to Garcia et al.: Common mistakes in measuring frequency-dependent word characteristics.

Authors:  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; Karine Megerdoomian; Matthew T McMahon; Brian F Tivnan; Christopher M Danforth
Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-21       Impact factor: 11.205

4.  Normative Emotional Responses to Behavior Analysis Jargon or How Not to Use Words to Win Friends and Influence People.

Authors:  Thomas S Critchfield; Karla J Doepke; L Kimberly Epting; Amel Becirevic; Derek D Reed; Daniel M Fienup; Jamie L Kremsreiter; Cheryl L Ecott
Journal:  Behav Anal Pract       Date:  2017-02-27

5.  Linguistic positivity in historical texts reflects dynamic environmental and psychological factors.

Authors:  Rumen Iliev; Joe Hoover; Morteza Dehghani; Robert Axelrod
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-21       Impact factor: 11.205

6.  Emotional Overtones of Behavior Analysis Terms in English and Five Other Languages.

Authors:  Thomas S Critchfield; Karla J Doepke
Journal:  Behav Anal Pract       Date:  2018-02-28

7.  History of art paintings through the lens of entropy and complexity.

Authors:  Higor Y D Sigaki; Matjaž Perc; Haroldo V Ribeiro
Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-27       Impact factor: 11.205

8.  Individuals with depression express more distorted thinking on social media.

Authors:  Krishna C Bathina; Marijn Ten Thij; Lorenzo Lorenzo-Luaces; Lauren A Rutter; Johan Bollen
Journal:  Nat Hum Behav       Date:  2021-02-11

9.  On the Social Validity of Behavior-Analytic Communication: a Call for Research and Description of One Method.

Authors:  Thomas S Critchfield; Amel Becirevic; Derek D Reed
Journal:  Anal Verbal Behav       Date:  2017-04-07

10.  How do you feel during the COVID-19 pandemic? A survey using psychological and linguistic self-report measures, and machine learning to investigate mental health, subjective experience, personality, and behaviour during the COVID-19 pandemic among university students.

Authors:  Cornelia Herbert; Alia El Bolock; Slim Abdennadher
Journal:  BMC Psychol       Date:  2021-06-02
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