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Tov, W., Ng, K.L., Lin, H., & Qiu, L. (2013). Detecting well-being via computerized content analysis of brief diary entries. Psychological Assessment, 25, 1069-1078. Abstract Two studies evaluated the correspondence between self-reported well-being and codings of emotion and life-content by the Linguistic Inquiry and Word Count (LIWC; Pennebaker, Booth, & Francis, 2011). Open-ended diary responses were collected from 206 participants daily for three weeks (Study 1) and 139 participants twice a week for eight weeks (Study 2). LIWC negative emotion consistently correlated with self-reported negative emotion. LIWC positive emotion correlated with self-reported positive emotion in Study 1 but not Study 2. No correlations were observed with global life satisfaction. Using a co-occurrence coding method to combine LIWC emotion codings with life-content codings, we estimated the frequency of positive and negative events in six life domains (family, friends, academics, health, leisure, and money). Domain-specific event frequencies predicted self-reported satisfaction in all domains in Study 1 but not consistently in Study 2. We suggest that the correspondence between LIWC codings and self-reported well-being is affected by the number of writing samples collected per day as well as the target period (e.g., past day vs. past week) assessed by the self-report measure. Extensions and possible implications for the analyses of similar types of open-ended data (e.g., social media messages) are discussed.[Download PDF] |