The aim of this chapter has been to provide a blueprint of research on language and personality up to this point that depicts both its structural soundness and need for additions and improvements. In closing, we will provide an overview of the existing studies in form of a summary table (see Table 2) and outline a few recommendations for future progress.
Table 2. Summary of Linguistic Indicators of Personality
Qualifier (e.g., Moderator)
second-person pronouns (+), first-person plural pronouns(+), positive emotion (+), social (+), leisure (+), sex (+), inhibition (-), tentativeness (-)
positivity (+), first-person singular pronouns(+), social (+), home (+), family (+), communication (+), death (-), money (-), swearing (-)
articles (+), prepositions (+), personal pronouns (-), family (-), home (-), rest (-)
Note. See text for references. For the Big Five, only the most common and universal correlates are listed.
Finding consistent threads among studies is sometimes made difficult by differing methodologies. Even among studies that used the same text analysis tool, some focused only on linguistic content rather than all categories, and others used different versions of a program that include several non-overlapping categories. The literature on language and personality would no doubt benefit from more comprehensive reporting of effects, in papers or in online supplemental materials. The existing studies suggest that both content and style categories are critical. Although content words are more susceptible to self-regulation and thus tend to be lower fidelity indicators of internal states, the degree to which a person’s language use fails to reflect their self-or informant-reported personality is often a telling indicator of self-regulatory personality processes and person x situation interactions (Baddeley, 2011; Baddeley & Pennebaker, 2012; Mehl et al., 2006; Mehl & Holleran, 2008). Style words are often more challenging to interpret, but are valuable as the mostly automatic, and therefore more psychologically representative, indicators of attentional focus and thinking styles (see Tausczik & Pennebaker, 2010). Content and style are two sides of a data-rich coin, and personality psychology has much to gain from increasingly considering both aspects of language use.
In order to correctly interpret the nature and true magnitude of effects, studies of language and personality may also need to increasingly measure and consider a range of potential moderators or modifiers, including facet-level trait measures (Yarkoni, 2010), individuals’ sex (Mehl et al., 2006), whether language use is public or private (Mehl & Holleran, 2008), the closeness of conversation partners (Baddeley, 2011) and linguistic co-occurrences (Gill & Oberlander, 2002). Specifically for function words, which are by definition extraordinarily versatile, research has shown that moderators matter. For example, whether I or you is said by a man or a woman and in the context of an angry or cheerful communication can dramatically influence which psychological processes those words reflect (Fast & Funder, 2010; Mehl et al., 2006; Tausczik & Pennebaker, 2010).
Context effects, such as the types of communication that a situation affords or demands, are important considerations in any area of behavioral research. Studies of language use are no exception. Just as a highly extraverted person would not be expected to behave dramatically differently than an introverted person in a situation lacking the potential for social interaction, personality traits that are predominantly defined by differences in social interaction are likely to leave fewer observable traces in solitary writing such as stream-of-consciousness essays. Furthermore, writing or speaking tasks that resemble criterion measures of personality (e.g., self-report personality questionnaires and essays describing one’s personality) are bound to be more highly correlated than naturalistic measures of language (e.g., Hirsh & Peterson, 2008). However, perhaps in part due to the influence of corpus linguistics, where language from a wide range of communication media are frequently compiled into a single dataset comprising billions of words, studies of linguistic indicators of personality have only recently come to seriously consider communication context. Given that so many personality dimensions hinge on how people react to and interact with others, it is particularly important – in studies of natural language use and beyond – for personality research to increasingly study the links between naturally occurring dialog, self-reports, and observer reports. As naturalistic language research expands with ongoing advances in audio recording technology and computer science methods, it should become easier to understand how linguistic signals are attenuated and warped by contextual influences such as experimental task, communication medium, and motivation.
The accomplishments of computerized text analysis in the last 15 years have been extraordinary. However, the software designers, programmers, and data analysts behind this revolution readily admit that there is room for improvement. Cohen and colleagues’ (2009) and S. Cohen’s (2011) research on the measurement of trait affect points to a possible need to improve word-count measurements of common positive emotion words, which are often used in ways that do not reflect positivity (e.g., I was pretty bored, someone like you), by considering their linguistic contexts. New discoveries made in function word categories that are new to the most recent version of LIWC (Pennebaker, Booth, & Francis, 20007) suggest that finer grained analyses based on words’ grammatical roles have the potential to clarify mixed results in past research and shed light on the cognitive mechanisms underlying personality dimensions.
Measures of within-text context – and the usability of tools that consider linguistic context – are bound to improve studies of language and personality as well. A word’s location in a text or sentence (Vine & Pennebaker, 2009) and its neighboring words (Gill & Oberlander, 2004) clearly matter but are rarely considered in psychological text analyses. Programs such as Latent Semantic Analysis (Landauer & Dumais, 1997) and WordSmith (Scott, 2008) handle such variables and, as they become more widely known and user-friendly, stand to greatly enrich future research.
In this famous monograph on personality, Allport (1937) wrote “language is a codification of common human experience, and by analyzing it much may be found that reflects the nature of human personality” (p. 373). Interestingly, the field of personality and language use only started getting serious momentum more than half a century later. As the research reviewed in this chapter reveals, though, the field is now rich, vibrant, and has already produced many important discoveries. We expect that the immense progress in (stationary and mobile) computing technology and parallel advances in computational linguistics will create a strong push for the field over the next years and lead to critical improvements in the complexity with which naturalistic language can be analyzed. It is our sense that the field will thrive to the extent that it uses these technologically-driven, “bottom-up”, analytic advances and, at the same time, balances them with innovative theoretical developments and clarifications from “top down”. To achieve this, it will undoubtedly become necessary for researchers from different fields to “cross-talk”. Social psychologists, personality psychologists, cognitive psychologists, linguists, communication scholars, computer scientists and other researchers will need to engage in conversations and collaborations and thereby transcend (and hopefully reduce) traditional discipline boundaries to more fully understand how our words reflect our selves.
1At some point, you may have received the following test over e-mail: “How many Fs does the following passage contain? ‘Finished files are the result of years of scientific study combined with the experience of years.’” Finding only three Fs tends to result from readers skipping ofs.
2The term sex is used by default to refer to all differences in personality-language links between men and women. However, gender may be more appropriate in cases where linguistic differences seem to be more strongly influenced by gender norms than biology (see Eagly, 1995).
Argamon, S., Koppel, M., Pennebaker, J. W., & Schler, J. (2009). Automatically profiling the author of an anonymous text. Communications of the ACM, 52, 119.
Augustine, A. A., Mehl, M. R., & Larsen, R. J., (2011). A positivity bias in written and spoken English, and its moderation by personality and gender. Social Psychology and Personality Science, 2, 508-515.
Baddeley, J. L., Beevers, C. G., & Pennebaker, J. W. (2012). Everyday social behavior during a major depressive episode. Manuscript under revision, Social Psychology and Personality Science. University of Texas at Austin, Austin, TX.
Baddeley, J. L. (2011). Email communications among people with and without major depressive disorder. Unpublished doctoral dissertation. University of Texas at Austin, Austin, TX.
Baddeley, J. L., & Singer, J. A. (2008). Telling losses: Personality correlates and functions of bereavement narratives. Journal of Research in Personality, 42, 421-438. doi:10.1016/j.jrp.2007.07.006
Bell, A., Brenier, J., Gregory, M., Girand, C., & Jurafsky, D. (2009). Predictability effects on durations of content and function words in conversational English. Journal of Memory and Language, 60, 92-111. Elsevier Inc. doi:10.1016/j.jml.2008.06.003
Bistricky, S. L., Ingram, R. E., & Atchley, R. A. (2011). Facial affect processing and depression susceptibility: Cognitive biases and cognitive neuroscience. Psychological Bulletin, 137, 998-1028. doi:10.1037/a0025348
Brown, P. & Levinson, S. C. (1987). Politeness: Some universals in language usage. Cambridge: Cambridge University Press.
Burke, P. A., & Dollinger, S. J. (2005). A picture’s worth a thousand words: Language use in autophotographic essay. Personality and Social Psychology Bulletin, 31, 536-548.
Campbell, W. K., & Miller, J. D. (2011). The Handbook of Narcissism and Narcissistic Personality Disorder: Theoretical Approaches, Empirical Findings, and Treatments. Hoboken, NJ: John Wiley & Sons.
Clark, H. H., & Brennan, S. A. (1991). Grounding in communication. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–149). Washington, DC: APA Books.
Cohen, A. S., Minor, K. S., Baillie, L. E., & Dahir, A. M. (2008). Clarifying the linguistic signature: Measuring personality from natural speech. Journal of Personality Assessment, 90, 559-563.
Cohen, A. S., Minor, K. S., Najolia, G. M., & Lee Hong, S. (2009). A laboratory-based procedure for measuring emotional expression from natural speech. Behavior Research Methods, 41, 204-12. doi:10.3758/BRM.41.1.204
Cohen, S. J. (2011). Measurement of negativity bias in personal narratives using corpus-based emotion dictionaries. Journal of Psycholinguistic Research,40: 119-135.
Costa, P. T., Jr., & McCrae, R. R. (1992). Normal personality assessment in clinical practice: The NEO Personality Inventory. Psychological Assessment, 4, 5-13.
Danner, D. D., Snowdon, D. A., & Friesen, W. V. (2002). Positive emotions in early life and longevity: Findings from the Nun Study. Journal of Personality and Social Psychology, 80, 804-813.
Davis, D., & Brock, T. C. (1975). Use of first-person pronouns as a function of increased objective self-awareness and performance feedback. Journal of Experimental Social Psychology, 11, 381-388.
Dewaele, J-M., & Furnham, A. (2000). Personality and speech production: A pilot study of second language learners. Personality and Individual Differences, 28, 355-365.
DeWall, C. N., Buffardi, L. E., Bonser, I., & Campbell, W. K. (2011). Narcissism and implicit attention seeking: Evidence from linguistic analyses of social networking and online presentation. Personality and Individual Differences, 51, 57-62.
DeWall, C. N., Pond, R. S., Campbell, W. K., & Twenge, J. M. (2011). Tuning in to psychological change: Linguistic markers of self-focus, loneliness, anger, antisocial behavior, and misery increase over time in popular U.S. song lyrics. Psychology of Aesthetics, Art, and Creativity.
Dodds, P. S., & Danforth, C. M. (2009). Measuring the happiness of large-scale written expression: Songs, blogs, and presidents. Journal of Happiness Studies, 11, 441-456. doi:10.1007/s10902-009-9150-9
Eagly, A. (1995). The science and politics of comparing women and men. American Psychologist, 50, 145-158.
Eastwick, P. W., Eagly, A. H., Finkel, E. J., & Johnson, S. E. (2011). Implicit and explicit preferences for physical attractiveness in a romantic partner: A double dissociation in predictive validity. Journal of Personality and Social Psychology, 101, 993-1011.
Fast, L. A, & Funder, D. C. (2008). Personality as manifest in word use: correlations with self-report, acquaintance report, and behavior. Journal of Personality and Social Psychology, 94, 334-46. doi:10.1037/0022-35220.127.116.114
Fast, L. A., & Funder, D. C. (2010). Gender differences in the correlates of self-referent word use: authority, entitlement, and depressive symptoms. Journal of Personality, 78, 313-38. doi:10.1111/j.1467-6494.2009.00617.x
Gill, A. J. & Oberlander, J. (2002). Taking care of the linguistic features of extraversion. Proceedings of the 24th Annual Conference of the Cognitive Science Society, 363—368.
Goldberg, L. R. (1981). Language and individual differences: The search for universals in personality lexicons. In L. Wheeler (Ed.), Review of personality and social psychology (pp. 141-165). Beverly Hills: Sage.
Goldenfeld, N., Baron-Cohen, S., & Wheelwright, S. (2007). Empathizing and systemizing in males, females, and autism: A test of the neural competition theory. Autism, 1-16.
Golder, S. A. & Macy, M. W. (2011). Diurnal and seasonal mood vary with work, sleep and daylength across diverse cultures. Science, 333, 1878-1881.
Gosling, S. D. (2008). Snoop: What your stuff says about you. New York: Basic books.
Gosling, S. D., Ko, S. J., Mannarelli, T., & Morris, M. E. (2002). A Room with a cue: Judgments of personality based on offices and bedrooms. Journal of Personality and Social Psychology, 82, 379-398.
Gottschalk, L. A., Gleser, G. C. (1969). Measurement of Psychological States Through the Content Analysis of Verbal Behaviour. Berkeley, CA: University of California Press.
Groom, C. J., & Pennebaker, J. W. (2005). The language of love: Sex, sexual orientation, and language use in online personal advertisements. Sex Roles, 52, 447-461. doi:10.1007/s11199-005-3711-0
Hancock, J., Curry, L., Goorha, S., & Woodworth, M. (2008). On lying and being lied to: A linguistic analysis of deception. Discourse Processes. 45:1-23.
Hart, R. P. (1984). Verbal style and the presidency: A computer-based analysis. New York: Academic Press.
Hirsh, J. B., & Peterson, J. B. (2009). Personality and language use in self-narratives. Journal of Research in Personality, 43(3), 524-527. doi:10.1016/j.jrp.2009.01.006
Holtgraves, T. (2011). Text messaging, personality, and the social context. Journal of Research in Personality, 45(1), 92-99. doi:10.1016/j.jrp.2010.11.015
Holtgraves, T. (2010). Social psychology and language: Words, utterances and conversations. In S. Fiske, D. Gilbert, & G. Lindzey (Eds.), Handbook of social psychology, 5th edition.
Holtzman, N. S., Vazire, S., & Mehl, M. R. (2010). Sounds like a narcissist: Behavioral manifestations of narcissism in everyday life. Journal of Research in Personality, 44, 478-484. doi:10.1016/j.jrp.2010.06.001
Ickes, W., & Reidhead, S., & Patterson, M. (1986). Machiavellianism and self-monitoring: As different as “me” and “you”. Social Cognition, 4, 58 – 74.
Jay, T. (2009). The utility and ubiquity of taboo words. Perspectives on Psychological Science, 4, 153–161.
Kacewicz, E., Pennebaker, J. W., Davis, M., Jeon, M., & Graesser, A. C. (in press, pending minor revision). The language of status hierarchies. Social Psychological and Personality Science.
Koppel, M., Argamon, S. & Shimoni, A. (2003), Automatically categorizing written texts by author gender. Literary and Linguistic Computing, 17, 401-412.
Kosinski, M. & Stillwell, D. (2012). myPersonality research wiki: myPersonality project. In http://www.mypersonality.org/wiki/.
Kramer, A. D. I. (2010). An unobtrusive behavioral model of “gross national happiness”. Proceedings of the 28th International Conference on Human Factors in Computing Systems - CHI, 287-290.
Küfner, A. C. P., Back, M. D., Nestler, S., & Egloff, B. (2010). Tell me a story and I will tell you who you are! Lens model analyses of personality and creative writing. Journal of Research in Personality, 44, 427-435. doi:10.1016/j.jrp.2010.05.003
Lakoff, R. T. (1975). Language and woman's place. New York: Harper & Row.
Landauer, T. K., and Dumais, S. T. (1997). A solution to Plato's problem: The Latent Semantic Analysis theory of the acquisition, induction, and representation of knowledge. Psychological Review, 104, 211-240
Lee, C. H., Kim, K., Seo, Y. S., & Chung, C. K. (2007). The relations between personality and language use. Journal of General Psychology, 134, 405-413.
Mairesse, F. & Walker, M. (2011). Controlling user perceptions of linguistic style: Trainable generation of personality traits. Computational Linguistics, 37, 445-488.
Mairesse, F., & Walker, M. A. (2006). Words mark the nerds : Computational models of personality recognition through language. Proceedings of the 28th Annual Conference of the Cognitive Science Society, 543–548.
Mairesse, F., Walker, M. A., Mehl, M. R., & Moore, R. K. (2007). Using linguistic cues for the automatic recognition of personality in conversation and text. Journal of Artificial Intelligence Research, 30, 457-500.
McAdams, D. P., & Pals, J. L. (2006). A new Big Five: Fundamental principles for an integrative science of personality. American Psychologist, 61, 204-17. doi:10.1037/0003-066X.61.3.204
Mehl, M. R. (2006a). Quantitative text analysis. In M. Eid & E. Diener (Eds.), Handbook of multimethod measurement in psychology (pp.141–156). Washington, DC: American Psychological Association.
Mehl, M. R. (2006b). The lay assessment of sub-clinical depression in daily life. Psychological Assessment, 18, 340-345.
Mehl, M. R., Gosling, S. D., & Pennebaker, J. W. (2006). Personality in its natural habitat: Manifestations and implicit folk theories of personality in daily life. Journal of Personality and Social Psychology, 90, 862-877.
Mehl, M. R. & Holleran, S. E. (2008). How taking a word for a word can be problematic: Context-dependent linguistic markers of extraversion and neuroticism. Paper presented at the 11th Conference of the International Association for Language and Social Psychology, Tucson, Arizona.
Mehl, M. R., & Pennebaker, J. W. (2003). The sounds of social life: A psychometric analysis of students’ daily social environments and natural conversations. Journal of Personality and Social Psychology, 84, 857-870.
Mehl, M., Pennebaker, J.W., Crow, D.M., Dabbs, J., & Price, J. (2001). The Electronically Activated Recorder (EAR): A device for sampling naturalistic daily activities and conversations. Behavior Research Methods, Instruments, & Computers, 33, 517-523.
Michel, J.-B., Shen, Y. K., Aiden, A. P., Veres, A., Gray, M. K., Te Google Books Team, Pickett, J. P., Hoiberg, D., Clancy, D., Norvig, P., Orwant, J., Pinker, S., Nowak, M. A., and Aiden, E. L. (2010). Quantitative analysis of culture using millions of digitized books. Science. doi: 10.1126/science.1199644
Newman, M. L., Groom, C. J., Handelman, L. D., & Pennebaker, J. W. (2008). Gender differences in language use: An analysis of 14,000 text samples. Discourse Processes, 45(3), 211-236. doi:10.1080/01638530802073712
Oberlander, J. & Gill, A.J. (2006). Language with character: A corpus-based study of individual differences in e-mail communication. Discourse Processes, 42, 239-270.
O‘Carroll Bantum, E., & Owen, J. E. (2009). Evaluating the validity of computerized content analysis programs for identification of emotional expression in cancer narratives. Psychological Assessment, 21, 79-88.
Paulhus, D.L. & Williams, K.M. (2002). The Dark Triad of personality: Narcissism, machiavellianism, and psychopathy. Journal of Research in Personality, 36, 556–563. doi:10.1016/S0092-6566(02)00505-6
Pennebaker, J. W. (2011). The secret life of pronouns: What our words say about us. New York: Bloomsbury Press.
Pennebaker, J. W. (1997). Opening up: The healing power of expressing emotion. New York: Guilford Press.
Pennebaker, J.W., Francis, M.E., & Booth, R.J. (2007). Linguistic Inquiry and Word Count (LIWC): LIWC 2007 [Computer program]. Austin, TX: LIWC.net.
Pennebaker, J. W. & Ireland, M. E. (2011). Using literature to understand authors: The case for computerized text analysis. Scientific Study of Literature, 1,34-48.
Pennebaker, J. W., & Lay, T. C. (2002). Language use and personality during crises: Analyses of mayor Rudolph Giuliani’s press conferences. Journal of Research in Personality, 36, 271-282.
Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G. (2003). Psychological aspects of natural language. use: Our words, our selves. Annual Review of Psychology, 54, 547-77.
Poole, M. E. (1979). Social class, sex, and linguistic coding. Language and Speech, 22, 49–67.
Pyszczynski, T., & Greenberg, J. (1987). Self-regulatory perseveration and the depressive self-focusing style: A self-awareness theory of reactive depression. Psychological Bulletin, 102, 122-138.
Qiu, L., Lin, H., Ramsay, J., & Yang, F. (2012). You are what you tweet: Personality expression and perception on Twitter. Journal of Research In Personality, 46, 710-718.
Ramírez-Esparza, N., Chung, C., Kacewicz, E., & Pennebaker, J. W. (2008). The Psychology of word use in depression forums in English and in Spanish: Testing two text analytic approaches. Proceedings of the International Conference on Weblogs and Social Media (ICWSM 2008).
Raskin, R., & Shaw, R. (1988). Narcissism and the use of personal pronouns. Journal of
Personality, 56, 2, 393-404.
Robbins, M. L., Focella, E. S., Kasle, S., Weihs, K. L., Lopez, A. M., & Mehl, M. R., (2011). Naturalistically observed swearing, emotional support and depressive symptoms in women coping with illness. Health Psychology, 30, 789-792.
Roccas, S., Sagiv, L., Schwartz, S. H., & Knafo, A. (2002). The Big Five personality factors and personal values. Personality and Social Psychology Bulletin, 28, 789-801. doi:10.1177/0146167202289008
Rodriguez, A. J., Holleran, S. E., & Mehl, M. R. (2010). Reading between the lines: The lay assessment of subclinical depression from written self-descriptions. Journal of Personality, 78, 575-98. doi:10.1111/j.1467-6494.2010.00627.x
Rohrbaugh, M. J., Mehl, M. R., Shoham, V., Reilly, E. S., & Ewy, G. a. (2008). Prognostic significance of spouse we talk in couples coping with heart failure. Journal of Consulting and Clinical Psychology, 76, 781–9.
Rude, S. S., Gortner, E.-M., & Pennebaker, J. W. (2004). Language use of depressed and depression-vulnerable college students. Cognition & Emotion, 18, 1121–1133.
Schaefer, D. R., Kornienko, O., & Fox, A. M. (2011). Misery does not love company: Network selection mechanisms and depression homophily. American Sociological Review, 76, 764-785.
Scherwitz, L., Canick, J. (1988). Self-reference and coronary heart disease risk. In K. Houston, & C. R. Snyder (Eds.), Type A behavior pattern: Research, theory, and intervention. New York: John Wiley & Sons.
Scherwitz, L., Graham, L. E., Ornish, D. (1985). Self-involvement and the risk factors for coronary heart disease. Advances, 2, 6 – 18.
Schmauder, A.R., Morris, R.K., & Poynor, D.V. (2000) Lexical processing and text integration of function and content words: Evidence from priming and eye fixations. Memory & Cognition, 7, 1098-1108.
Schnurr, P. P., Rosenberg, S. D., Oxman, T. E., & Tucker, G. J. (1986). A methodological note on content analysis: Estimates of reliability. Journal of Personality Assessment, 50, 601-609.
Schwartz, H. A. Eichstaedt, J., Dziurzynski, L., Kern, M., Blanco, E., Kosinski, M. Stillwell, D., Seligman, M., & Ungar, L. H.. (2013). Toward personality insights from language exploration in social media. AAAI-2013 Spring Symposium: Analyzing Microtext. Stanford, California.
Scott, M., 2008, WordSmith Tools version 5, Liverpool: Lexical Analysis Software.
Simmons, R. A., Gordon, P. C., & Chambless, D. L. (2005). Pronouns in marital interaction. Psychological Science, 16, 932-6.
Simmons, R. a, Chambless, D. L., & Gordon, P. C. (2008). How do hostile and emotionally overinvolved relatives view relationships? What relatives’ pronoun use tells us. Family Process, 47, 405–19.
Slatcher, R. B., Chung, C. K., Pennebaker, J. W., & Stone, L. D. (2007). Winning words: Individual differences in linguistic style among U.S. presidential and vice presidential candidates. Journal of Research in Personality, 41, 63-75.
Smith, C. P. (Ed.). (1992). Motivation and personality: Handbook of thematic content analysis. Cambridge, MA: Cambridge University Press.
Stirman, S.W., & Pennebaker, J.W. (2001). Word use in the poetry of suicidal and non-suicidal poets. Psychosomatic Medicine 63, 517-522.
Stone, P. J., Dunphy, D. C., Smith, M. S., & Ogilvie, D. M. (1966). The general inquirer: A computer approach to content analysis. Cambridge: MIT Press.
Tanenhaus, M.K. & Trueswell, J.C. (1995). Sentence comprehension. In Eimas & Miller (Eds.) Handbook in Perception and Cognition, Volume 11: Speech Language and Communication, pp. 217-262. New York: Academic Press.
Tausczik, Y. R., & Pennebaker, J. W. (2009). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29, 24-54. doi:10.1177/0261927X09351676
Teasdale, J. D. (1988). Cognitive vulnerability to persistent depression. Cognition and Emotion, 2, 247-274.
Teasdale, J. D., & Green, H. A. C. (2004). Ruminative self-focus and autobiographical memory. Personality and Individual Differences, 36, 1933–1943.
Townsend, D. J. & Saltz, E. (1972). Phrases vs. meaning in the immediate recall of sentences. Psychonomic Science, 29, 381-384.
Trzesniewski, K.H. & Donnellan, M.B. (2010). Rethinking “Generation Me”: A study of cohort effects from 1976–2006. Perspectives in Psychological Science, 5, 58–75.
Vazire, S., & Gosling, S. D. (2004). e-Perceptions: personality impressions based on personal websites. Journal of personality and social psychology, 87, 123-32.
Vine, V. & Pennebaker, J. W. (2009). [The arc of narrative project]. Unpublished raw data. University of Texas at Austin, Austin, TX.
Watson, D. & Pennebaker, J. W. (1989). Health complaints, stress, and disease: Exploring the central role of negative affectivity. Psychological Review, 96, 234-254.
Weintraub, W. (1981). Verbal behavior: Adaptation and psychopathology. New York: Springer.
Yarkoni, T. (2010). Personality in 100,000 Words: A large-scale analysis of personality and word use among bloggers. Journal of Research in Personality, 44, 363-373. Elsevier Inc. doi:10.1016/j.jrp.2010.04.001