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

• Main Authors: TOV, William, NG, Kok Leong, LIN, Han, QIU, Lin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: well-being; emotion; satisfaction; content analysis; linguistic analysis; Social Psychology
• Online Access: https://ink.library.smu.edu.sg/soss_research/1499; https://ink.library.smu.edu.sg/context/soss_research/article/2755/viewcontent/Detecting_well_being_via_computerized_content_analysis_of_brief_diary_entries.pdf
• Institution: Singapore Management University

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 emotion 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.