Detecting Well-Being via Computerized Content Analysis of Brief Diary Entries

Psychological Assessment, 25, 1069-1078.

36 Pages Posted: 19 Feb 2014

See all articles by William Tov

William Tov

Singapore Management University

Kok Leong Ng

University of Kentucky

Han Lin

Nanyang Technological University (NTU)

Lin Qiu

Nanyang Technological University (NTU)

Date Written: December 1, 2013

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.

Keywords: well-being, emotion, satisfaction, content analysis, linguistic analysis

JEL Classification: I31

Suggested Citation

Tov, William and Ng, Kok Leong and Lin, Han and Qiu, Lin, Detecting Well-Being via Computerized Content Analysis of Brief Diary Entries (December 1, 2013). Psychological Assessment, 25, 1069-1078. , Available at SSRN: https://ssrn.com/abstract=2397674

William Tov (Contact Author)

Singapore Management University ( email )

90 Stamford Road
Level 4
Singapore, 178903
Singapore

Kok Leong Ng

University of Kentucky ( email )

Lexington, KY 40506
United States

Han Lin

Nanyang Technological University (NTU) ( email )

S3 B2-A28 Nanyang Avenue
Singapore, 639798
Singapore

Lin Qiu

Nanyang Technological University (NTU) ( email )

S3 B2-A28 Nanyang Avenue
Singapore, 639798
Singapore

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