We analyzed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age. In our open-vocabulary technique, the data itself drives a comprehensive exploration of language that distinguishes people, finding connections that are not captured with traditional closed-vocabulary word-category analyses. Our analyses shed new light on psychosocial processes yielding results that are face valid (e.g., subjects living in high elevations talk about the mountains), tie in with other research (e.g., neurotic people disproportionately use the phrase ‘sick of’ and the word ‘depressed’), suggest new hypotheses (e.g., an active life implies emotional stability), and give detailed insights (males use the possessive ‘my’ when mentioning their ‘wife’ or ‘girlfriend’ more often than females use ‘my’ with ‘husband’ or 'boyfriend’). To date, this represents the largest study, by an order of magnitude, of language and personality.

In the book Flourish (2011), Seligman defined wellbeing in terms of five pillars: Positive emotion, Engagement, Relationships, Meaning, and Accomplishment, or PERMA. We developed the PERMA-Profiler as a brief measure of PERMA. We first compiled hundreds of theoretically relevant items. Three studies (N = 7,188) reduced, tested, and refined items, resulting in a final set of 15 questions (three items per PERMA domain). Eight additional filler items were added, which assess overall wellbeing, negative emotion, loneliness, and physical health, resulting in a final 23item measure. A series of eight additional studies (N = 31,966) were conducted to test the psychometrics of the measure. The PERMA-Profiler demonstrates acceptable model fit, internal and cross-time consistency, and evidence for content, convergent, and divergent validity. Scores are reported visually as a profile across domains, reflecting the multidimensional nature of flourishing. The PERMA-Profiler adds to the toolbox of wellbeing measures, allowing individuals to monitor their wellbeing across multiple psychosocial domains.

There is extraordinary diversity in how the construct of self-control is operationalized in research studies. We meta-analytically examined evidence of convergent validity among executive function, delay of gratification, and self- and informant-report questionnaire measures of self-control. Overall, measures demonstrated moderate convergence (rrandom = .27 [95% CI = .24, .30]; rfixed = .34 [.33, .35], k = 282 samples, N = 33,564 participants), although there was substantial heterogeneity in the observed correlations. Correlations within and across types of self-control measures were strongest for informant-report questionnaires and weakest for executive function tasks. Questionnaires assessing sensation seeking impulses could be distinguished from questionnaires assessing processes of impulse regulation. We conclude that self-control is a coherent but multidimensional construct best assessed using multiple methods.

Language use is a psychologically rich, stable individual difference with well-established correlations to personality. We describe a method for assessing personality using an open-vocabulary analysis of language from social media. We compiled the written language from 66,732 Facebook users and their questionnaire-based self-reported Big Five personality traits, and then we built a predictive model of personality based on their language. We used this model to predict the 5 personality factors in a separate sample of 4,824 Facebook users, examining (a) convergence with self-reports of personality at the domain- and facet-level; (b) discriminant validity between predictions of distinct traits; (c) agreement with informant reports of personality; (d) patterns of correlations with external criteria (e.g., number of friends, political attitudes, impulsiveness); and (e) test-retest reliability over 6-month intervals. Results indicated that language-based assessments can constitute valid personality measures: they agreed with self-reports and informant reports of personality, added incremental validity over informant reports, adequately discriminated between traits, exhibited patterns of correlations with external criteria similar to those found with self-reported personality, and were stable over 6-month intervals. Analysis of predictive language can provide rich portraits of the mental life associated with traits. This approach can complement and extend traditional methods, providing researchers with an additional measure that can quickly and cheaply assess large groups of participants with minimal burden.

No abstract