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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
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Language measures correlate with other measures used to study emotion.

Shaina Munin1, Desmond C Ong1, Sydney Okland1

  • 1Department of Psychology, The University of Texas at Austin, Austin, TX, USA.

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Language measures, particularly those assessing valence, correlate with observer and self-reports of emotion. This suggests language can be a valuable tool for emotion research when other methods are impractical.

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Area of Science:

  • Psychology
  • Linguistics
  • Affective Science

Background:

  • Language analysis is increasingly used to study emotion.
  • Previous research primarily focused on language and self-report correlations.
  • The relationship between language and other emotion measures remains less understood.

Purpose of the Study:

  • To investigate the associations between language measures and a wider array of emotion indicators.
  • To examine these associations across various established linguistic dictionaries.
  • To determine the consistency of these relationships in multimodal datasets.

Main Methods:

  • Analysis of three large, multimodal datasets with varying participant numbers and text lengths.
  • Testing associations between language-derived emotion (valence and discrete emotions) and self-report, observer report, facial cues, and vocal cues.
  • Comparison of results across multiple dictionaries (LIWC-22, NRC, Lexical Suite, ANEW, VADER).

Main Results:

  • Language measures consistently correlated with observer and self-report measures across datasets.
  • Significant associations were found between language measures of valence and facial cues, but not discrete emotions.
  • Language measures did not consistently associate with vocal cues.
  • Dictionary choice did not significantly impact the observed associations.

Conclusions:

  • Language measures, especially those indicating valence, show robust correlations with multiple other emotion assessment methods.
  • Language analysis offers a viable and practical approach for emotion research, particularly when other data modalities are limited.
  • Researchers can confidently employ language analysis to study emotion, complementing or substituting traditional methods.