The words people use in their daily lives can reveal important aspects of their social and psychological worlds. With advances in computer technology, text analysis allows researchers to reliably and quickly assess features of what people say as well as subtleties in their linguistic styles. Following a brief review of several text analysis programs, we summarize some of the evidence that links natural word use to personality, social and situational fluctuations, and psychological interventions. Of particular interest are findings that point to the psychological value of studying particles-parts of speech that include pronouns, articles, prepositions, conjunctives, and auxiliary verbs. Particles, which serve as the glue that holds nouns and regular verbs together, can serve as markers of emotional state, social identity, and cognitive styles.

To examine the expression of personality in its natural habitat, the authors tracked 96 participants over 2 days using the Electronically Activated Recorder (EAR), which samples snippets of ambient sounds in participants' immediate environments. Participants' Big Five scores were correlated with EAR-derived information on their daily social interactions, locations, activities, moods, and language use; these quotidian manifestations were generally consistent with the trait definitions and (except for Openness) often gender specific. To identify implicit folk theories about daily manifestations of personality, the authors correlated the EAR-derived information with impressions of participants based on their EAR sounds; judges' implicit folk theories were generally accurate (especially for Extraversion) and also partially gender specific. The findings point to the importance of naturalistic observation studies on how personality is expressed and perceived in the natural stream of everyday behavior.

It is well known that utterances convey a great deal of information about the speaker in addition to their semantic content. One such type of information consists of cues to the speaker's personality traits, the most fundamental dimension of variation between humans. Recent work explores the automatic detection of other types of pragmatic variation in text and conversation, such as emotion, deception, speaker charisma, dominance, point of view, subjectivity, opinion and sentiment. Personality affects these other aspects of linguistic production, and thus personality recognition may be useful for these tasks, in addition to many other potential applications. However, to date, there is little work on the automatic recognition of personality traits. This article reports experimental results for recognition of all Big Five personality traits, in both conversation and text, utilising both self and observer ratings of personality. While other work reports classification results, we experiment with classification, regression and ranking models. For each model, we analyse the effect of different feature sets on accuracy. Results show that for some traits, any type of statistical model performs significantly better than the baseline, but ranking models perform best overall. We also present an experiment suggesting that ranking models are more accurate than multi-class classifiers for modelling personality. In addition, recognition models trained on observed personality perform better than models trained using selfreports, and the optimal feature set depends on the personality trait. A qualitative analysis of the learned models confirms previous findings linking language and personality, while revealing many new linguistic markers.

The diaries of 1,084 U.S. users of an on-line journaling service were downloaded for a period of 4 months spanning the 2 months prior to and after the September 11 attacks. Linguistic analyses of the journal entries revealed pronounced psychological changes in response to the attacks. In the short term, participants expressed more negative emotions, were more cognitively and socially engaged, and wrote with greater psychological distance. After 2 weeks, their moods and social referencing returned to baseline, and their use of cognitive-analytic words dropped below baseline. Over the next 6 weeks, social referencing decreased, and psychological distancing remained elevated relative to baseline. Although the effects were generally stronger for individuals highly preoccupied with September 11, even participants who hardly wrote about the events showed comparable language changes. This study bypasses many of the methodological obstacles of trauma research and provides a fine-grained analysis of the time line of human coping with upheaval.

A recording device called the Electronically Activated Recorder (EAR) is described. The EAR taperecords for 30 sec once every 12 min for 2-4 days. It is lightweight and portable, and it can be worn comfortably by participants in their natural environment. The acoustic data samples provide a nonobtrusive record of the language used and settings entered by the participant. Preliminary psychometric findings suggest that the EAR data accurately reflect individuals' natural social, linguistic, and psychological lives. The data presented in this article were collected with a first-generationEAR systembased on analog tape recording technology, but a second generation digital EAR is now available.