Detecting well-being via computerized content analysis of brief diary entries

William Tov, Kok Leong Ng, Han Lin, Lin Qiu
<span title="">2013</span> <i title="American Psychological Association (APA)"> <a target="_blank" rel="noopener" href="" style="color: black;">Psychological Assessment</a> </i> &nbsp;
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 3 weeks (Study 1) and from 139 participants twice a week for 8 weeks (Study 2). LIWC negative emotion consistently correlated with self-reported negative emotion. LIWC positive emotion correlated with self-reported positive
more &raquo; ... otion in Study 1 but not in 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 6 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1037/a0033007</a> <a target="_blank" rel="external noopener" href="">pmid:23730828</a> <a target="_blank" rel="external noopener" href="">fatcat:kiwzweaox5brtd5djvxu6kajiy</a> </span>
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