Pang, Dandan; Eichstaedt, Johannes C.; Buffone, Anneke; Slaff, Barry; Ruch, Willibald; Ungar, Lyle H. (2020). The language of character strengths: Predicting morally valued traits on social media. Journal of personality, 88(2), pp. 287-306. Wiley-Blackwell 10.1111/jopy.12491
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Objective: Social media is increasingly being used to study psychological constructs. This study is the first to use Twitter language to investigate the 24 Values in Action Inventory of Character Strengths, which have been shown to predict important life domains such as well‐being.
Method: We use both a top‐down closed‐vocabulary (Linguistic Inquiry and Word Count) and a data‐driven open‐vocabulary (Differential Language Analysis) approach to analyze 3,937,768 tweets from 4,423 participants (64.3% female), who answered a 240‐item survey on character strengths.
Results: We present the language profiles of (a) a global positivity factor accounting for 36% of the variances in the strengths, and (b) each of the 24 individual strengths, for which we find largely face‐valid language associations. Machine learning models trained on language data to predict character strengths reach out‐of‐sample prediction accuracies comparable to previous work on personality (r median = 0.28, ranging from 0.13 to 0.51).
Conclusions: The findings suggest that Twitter can be used to characterize and predict character strengths. This technique could be used to measure the character strengths of large populations unobtrusively and cost‐effectively.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
07 Faculty of Human Sciences > Institute of Psychology > Work and Organisational Psychology |
UniBE Contributor: |
Pang, Dandan |
Subjects: |
100 Philosophy > 150 Psychology 300 Social sciences, sociology & anthropology |
ISSN: |
0022-3506 |
Publisher: |
Wiley-Blackwell |
Funders: |
[4] Swiss National Science Foundation ; [UNSPECIFIED] Templeton Religion Trust |
Language: |
English |
Submitter: |
Dandan Pang |
Date Deposited: |
19 Jul 2019 09:10 |
Last Modified: |
17 Jun 2023 23:08 |
Publisher DOI: |
10.1111/jopy.12491 |
PubMed ID: |
31107975 |
Uncontrolled Keywords: |
character strengths; language analysis; social media; Values in Action survey; well‐being |
BORIS DOI: |
10.7892/boris.131199 |
URI: |
https://boris.unibe.ch/id/eprint/131199 |