Personality in its natural habitat: manifestations and implicit folk theories of personality in daily life.

By Matthias R. Mehl, Samuel D. Gosling, James W. Pennebaker. Journal of Personality and Social Psychology, 2006

742 citations recorded by the source corpus.

Subfields: Clinical Psychology, Experimental and Cognitive Psychology, Literature and Literary Theory

View Paper: https://www.semanticscholar.org/paper/d5a501dfe9e04c6608f0a405f0bae22d11e8eb94

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Citations in the corpus

Trainable Generation of Big-Five Personality Styles through Data-Driven Parameter Estimation (2008, methodology): “These parameters are derived from psychological studies identifying linguistic markers of the Big Five traits (Pennebaker and King, 1999; Mehl et al., 2006, inter alia ).”
Psychology as the Science of Self-Reports and Finger Movements: Whatever Happened to Actual Behavior? (2007, background): “We suspect that more than one social psychologist was inspired onto his or her career by an undergraduate class lecture on John Darley’s and Bibb Latané’s studies of bystander intervention (e.g., Darley & Latané, 1968) or on Stanley Milgram’s (1975) obedience studies, which put real people into em”
Paradigm shift to the integrative Big Five trait taxonomy: History, measurement, and conceptual issues. (2008, background): “In a study monitoring students’ daily life (Mehl, Gosling, & Pennebaker, 2006), students high in Conscientiousness spent more time in the classroom or on campus; students high in Openness spent more time in coffee houses and restaurants; and students high in Extraversion engaged in more…”
Measuring Personality Constructs: The Advantages and Disadvantages of Self-Reports, Informant Reports and Behavioural Assessments (2008, background): “Mehl, Gosling, and Pennebaker (2006) collected auditory EAR clips of individuals’ lives over the span of a couple of days, and had research assistants code the sounds on a number of variables including interaction types (e.g.”
Motivating Personality-aware Machine Translation (2015, background): “Yet, studies have shown that traits can be reliably detected following cold readings of texts from unknown authors (Mehl et al., 2006; Gill et al., 2012) without such explicit knowledge.”
Automatic personality assessment through social media language. (2015, methodology): “…yielded an impressive body of evidence linking language to personality (e.g., Cohen, Minor, Baillie, & Dahir, 2008; Fast & Funder, 2008; Hirsh & Peterson, 2009; Lee, Kim, Seo, & Chung, 2007; Mehl, Gosling, & Pennebaker, 2006; Pennebaker, Mehl, & Niederhoffer, 2003; Tausczik & Pennebaker, 2010).”
Hormones and personality: Testosterone as a marker of individual differences (2007, neutral): “Researchers have begun to use methods such as laboratory-based (Borkenau, Mauer, Riemann, Spinath, & Angleitner, 2004; Funder, Furr, & Colvin, 2000) or naturalistic observation ( Mehl, Gosling, & Pennebaker, in press; Mehl & Pennebaker, 2003), linguistic analyses (Pennebaker & King, 1999), informan”
Personality in 100,000 Words: A large-scale analysis of personality and word use among bloggers (2010, methodology): “Indeed, the single largest correlation between any LIWC category and Big Five trait was .23 (Figure S4)—a magnitude close to the mean statistically significant effect size found in some previous studies (Fast & Funder, 2008; Hirsh & Peterson, 2009; Mehl et al., 2006).”
The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods (2010, positive): “Studies measuring personality in participants through writing samples (Pennebaker & King, 1999) and spoken dialogue (Mehl, Gosling, & Pennebaker, 2006) have shown that some LIWC categories correspond with big-five personality traits.”
Text messaging, personality, and the social context (2011, background): “In contrast to prior research (Mehl et al., 2006), extraversion was not related to amount of swearing.”
A Survey of Personality Computing (2014, neutral): “The same work presents similar experiments over the Electronically Activated Recorder (EAR) corpus [50], a collection of random conversation snippets involving 96 subjects.”