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

Objectives Narcissism 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....

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Published in:Journals of Gerontology Series B: Psychological Sciences & Social Sciences Vol. 78; no. 9; pp. 1493 - 1501
Main Authors: Zhang, Shiyang, Fingerman, Karen L, Birditt, Kira S
Format: Article
Published: Oxford University Press / USA Sep2023
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Sep2023
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      pub: Oxford University Press / USA
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        atl: Detecting Narcissism From Older Adults' Daily Language Use: A Machine Learning Approach.
      aug:
        au:
          Zhang, Shiyang
          Fingerman, Karen L
          Birditt, Kira S
        affil:
          Department of Human Development and Family Sciences, The University of Texas at Austin , Austin, Texas , USA
          Institute for Social Research, University of Michigan , Ann Arbor, Michigan , USA
      su:
        Texas
        Narcissism
        Linguistics
        Self-evaluation
        Interviewing
        Interpersonal relations
        Personality tests
        Personality assessment
        Old age
        Statistics
        Speech evaluation
        Machine learning
        Random forest algorithms
        Descriptive statistics
        Independent living
        Questionnaires
        Research funding
        Data analysis
        Statistical models
        Algorithms
        Poisson distribution
      sug:
        subj:
          Narcissism
          Linguistics
          Self-evaluation
          Interviewing
          Interpersonal relations
          Personality tests
          Personality assessment
          Old age
          Texas
          Statistics
          Speech evaluation
          Machine learning
          Random forest algorithms
          Descriptive statistics
          Independent living
          Questionnaires
          Research funding
          Data analysis
          Statistical models
          Algorithms
          Poisson distribution
      keyword:
        Electronically activated recorder (EAR)
        Linguistic features
        personality
        Electronically activated recorder (EAR)
        Linguistic features
        personality
      ab: Objectives Narcissism 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. Methods Participants 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. Results The 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). Discussion Narcissism 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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