Bridging minds and machines: Unmasking the limits in text‐based automatic personality recognition for enhanced psychology–AI synergy.

Text‐based automatic personality recognition (APR) operates at the intersection of artificial intelligence (AI) and psychology to determine the personality of an individual from their text sample. This covert form of personality assessment is key for a variety of online applications that contribute...

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Publicado en:British Journal of Psychology Vol. 117; no. 2; pp. 702 - 725
Autores principales: Bhandarkar, Avanti, Wilson, Ronald, Swarup, Anushka, Webster, Gregory D., Woodard, Damon
Formato: Artículo
Publicado: Wiley-Blackwell May2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Bridging minds and machines: Unmasking the limits in text‐based automatic personality recognition for enhanced psychology–AI synergy.
      aug:
        au:
          Bhandarkar, Avanti
          Wilson, Ronald
          Swarup, Anushka
          Webster, Gregory D.
          Woodard, Damon
        affil:
          Florida Institute for National Security (FINS), Gainesville Florida,, USA
          Department of Psychology, University of Florida, Gainesville Florida,, USA
      su:
        Language & languages
        Speech
        Artificial intelligence
        Personality assessment
        Psychology
        Psycholinguistics
        Psychometrics
        Personality
        Personality tests
        Conceptual models
        Data mining
        Benchmarking (Management)
        Natural language processing
        Machine learning
        Text messages
        Algorithms
      sug:
        subj:
          Language & languages
          Speech
          Artificial intelligence
          Personality assessment
          Psychology
          Psycholinguistics
          Psychometrics
          Personality
          Personality tests
          Wireless Telecommunications Carriers (except Satellite)
          Conceptual models
          Data mining
          Benchmarking (Management)
          Natural language processing
          Machine learning
          Text messages
          Algorithms
      keyword:
        automatic personality recognition
        big five
        dark triad
        human–AI teaming
        lexical hypothesis
        automatic personality recognition
        big five
        dark triad
        human–AI teaming
        lexical hypothesis
      ab: Text‐based automatic personality recognition (APR) operates at the intersection of artificial intelligence (AI) and psychology to determine the personality of an individual from their text sample. This covert form of personality assessment is key for a variety of online applications that contribute to individual convenience and well‐being such as that of chatbots and personal assistants. Despite the availability of good quality data utilizing state‐of‐the‐art AI methods, the reported performance of these recognition systems remains below expectations in comparable areas. Consequently, this work investigates and identifies the source of this performance limit and attributes it to the flawed assumptions of text‐based APR. These insights are obtained via a large‐scale comprehensive benchmark and analysis of text data from five corpora with diverse characteristics and complementary personality models (Big Five and Dark Triad) applied to an assortment of AI methods ranging from hand‐crafted linguistic features to data‐driven transformers. Finally, the work concludes by identifying the open problems that can help navigate the limitations in text‐based automatic personality recognition to a great extent.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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