We are in the midst of a technological revolution whereby, for the first time, researchers can link daily word use to a broad array of real-world behaviors. This article reviews several computerized text analysis methods and describes how Linguistic Inquiry and Word Count (LIWC) was created and validated. LIWC is a transparent text analysis program that counts words in psychologically meaningful categories. Empirical results using LIWC demonstrate its ability to detect meaning in a wide variety of experimental settings, including to show attentional focus, emotionality, social relationships, thinking styles, and individual differences.
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.
Telling lies often requires creating a story about an experience or attitude that does not exist. As a result, false stories may be qualitatively different from true stories. The current project investigated the features of linguistic style that distinguish between true and false stories. In an analysis of five independent samples, a computer-based text analysis program correctly classified liars and truth-tellers at a rate of 67% when the topic was constant and a rate of 61% overall. Compared to truth-tellers, liars showed lower cognitive complexity, used fewer self-references and other-references, and used more negative emotion words.
30 September 1999 in Journal of Clinical Psychology
Essays written by currently-depressed, formerly-depressed, and never-depressed college students were examined for differences in language that might shed light on the cognitive operations associated with depression and depression-vulnerability. A text analysis program computed the incidence of words in predesignated categories. Consistent with Beck's cognitive model and with Pyczsinski and Greenberg's self-focus model of depression, depressed participants used more negatively valenced words and used the word, "I" more than did never-depressed participants. Formerly-depressed (presumably depression-vulnerable) participants did not differ from never-depressed participants on these indices of depressive processing. However, consistent with prediction, formerly-depressed participants' use of the word "I" increased across the essays and was significantly greater than that of never-depressed writers in the final portion of the essays.