Literature DB >> 25313685

Affective biases in English are bi-dimensional.

Amy Beth Warriner1, Victor Kuperman.   

Abstract

A long-standing observation about the interface between emotion and language is that positive words are used more frequently than negative ones, leading to the Pollyanna hypothesis which alleges a predominantly optimistic outlook in humans. This paper uses the largest available collection of affective ratings as well as insights from linguistics to revisit the Pollyanna hypothesis as it relates to two dimensions of emotion: valence (pleasantness) and arousal (intensity). We identified systematic patterns in the distribution of words over a bi-dimensional affective space, which (1) run counter to and supersede most prior accounts, and (2) differ drastically between word types (unique, distinct words in the lexicon) and word tokens (number of occurrences of available words in the lexicon). We argue for two factors that shape affect in language and society: a pro-social benevolent communication strategy with its emphasis on useful and dangerous phenomena, and the structure of human subjective perception of affect.

Entities:  

Keywords:  Arousal; Cognitive bias; Lexicon; Subjective experience; Valence

Mesh:

Year:  2014        PMID: 25313685     DOI: 10.1080/02699931.2014.968098

Source DB:  PubMed          Journal:  Cogn Emot        ISSN: 0269-9931


  9 in total

1.  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

2.  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

3.  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

4.  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

5.  Norms for 10,491 Spanish words for five discrete emotions: Happiness, disgust, anger, fear, and sadness.

Authors:  Hans Stadthagen-González; Pilar Ferré; Miguel A Pérez-Sánchez; Constance Imbault; José Antonio Hinojosa
Journal:  Behav Res Methods       Date:  2018-10

6.  Sliding into happiness: A new tool for measuring affective responses to words.

Authors:  Amy Beth Warriner; David I Shore; Louis A Schmidt; Constance L Imbault; Victor Kuperman
Journal:  Can J Exp Psychol       Date:  2017-03

7.  Human language reveals a universal positivity bias.

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:  2015-02-09       Impact factor: 11.205

8.  It's all in the delivery: Effects of context valence, arousal, and concreteness on visual word processing.

Authors:  Bryor Snefjella; Victor Kuperman
Journal:  Cognition       Date:  2016-08-24

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
  9 in total

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