Detecting Narcissism From Older Adults’ Daily Language Use: A Machine Learning Approach

Shiyang Zhang, Karen L Fingerman, Kira S Birditt and Rodlescia Sneed

The Journals of Gerontology: Series B, 2023, vol. 78, issue 9, 1493-1500

Abstract: ObjectivesNarcissism has been associated with poorer quality social connections in late life, yet less is known about how narcissism is associated with older adults’ daily social interactions. This study explored the associations between narcissism and older adults’ language use throughout the day.MethodsParticipants aged 65–89 (N = 281) wore electronically activated recorders which captured ambient sound for 30 s every 7 min across 5–6 days. Participants also completed the Narcissism Personality Inventory-16 scale. We used Linguistic Inquiry and Word Count to extract 81 linguistic features from sound snippets and applied a supervised machine learning algorithm (random forest) to evaluate the strength of links between narcissism and each linguistic feature.ResultsThe random forest model showed that the top 5 linguistic categories that displayed the strongest associations with narcissism were first-person plural pronouns (e.g., we), words related to achievement (e.g., win, success), to work (e.g., hiring, office), to sex (e.g., erotic, condom), and that signal desired state (e.g., want, need).DiscussionNarcissism may be demonstrated in everyday life via word use in conversation. More narcissistic individuals may have poorer quality social connections because their communication conveys an emphasis on self and achievement rather than affiliation or topics of interest to the other party.

Keywords: Electronically activated recorder (EAR); Linguistic features; personality (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1093/geronb/gbad061 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:geronb:v:78:y:2023:i:9:p:1493-1500.

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

The Journals of Gerontology: Series B is currently edited by Psychological Sciences - S. Duke Han, PhD and Social Sciences - Jessica A Kelley, PhD, FGSA

More articles in The Journals of Gerontology: Series B from The Gerontological Society of America Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().