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Automatic personality assessment through social media language.

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Analyzing social media language offers a valid method for personality assessment. This approach accurately predicts personality traits and demonstrates stability over time.

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Area of Science:

  • Psychological science
  • Computational social science
  • Personality psychology

Background:

  • Language use is a key individual difference linked to personality.
  • Traditional personality assessments can be time-consuming and burdensome.

Purpose of the Study:

  • To develop and validate a method for assessing personality using open-vocabulary language analysis from social media.
  • To evaluate the reliability, validity, and external correlations of language-based personality measures.

Main Methods:

  • Compiled language data from 66,732 Facebook users and their Big Five personality traits.
  • Built a predictive model of personality based on language.
  • Validated the model in a separate sample of 4,824 users, assessing convergence, discriminant validity, informant agreement, external criteria correlations, and test-retest reliability.

Main Results:

  • Language-based assessments demonstrated validity, agreeing with self- and informant reports.
  • The method showed discriminant validity between traits and stable correlations with external criteria.
  • Test-retest reliability was confirmed over 6-month intervals.

Conclusions:

  • Language analysis from social media provides a valid, reliable, and efficient tool for personality assessment.
  • This approach complements traditional methods, offering a low-burden way to assess large populations.
  • Predictive language analysis offers insights into the psychological landscape associated with personality traits.