Inferring Grandiose Narcissism From Text
Liwc Versus Machine Learning
Dados Bibliográficos
| ID | 18985646 |
|---|---|
| Autores | Andrew D Cutler (0000-0002-6616-8522, Boston University, Boston, MA, USA, autor correspondente), Stephen W Carden (0000-0002-4793-7883, Georgia Southern University, Statesboro, GA, USA), Hannah L Dorough (Georgia Southern University, Statesboro, GA, USA), Nicholas S Holtzman (0000-0003-0392-0083, Georgia Southern University, Statesboro, GA, USA) |
| Ano | 2021 |
| Volume | 40 |
| Fascículo | 2 |
| Páginas | 260-276 |
| Data de publicação | 2021-03-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Journal of Language and Social Psychology (JOURNAL) |
| Identificadores do periódico | ISSN: 0261-927X • E-ISSN: 1552-6526 |
| Editora | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/0261927x20936309 |
| OpenAlex | W3039423604 |
| Idioma | EN |
| Citações recebidas | 4 |
| Referências citadas | 50 |
People have long used language to infer associates’ personality. In quantitative research, the relationship is often analyzed by looking at correlations between a psychological construct and the Linguistic Inquiry and Word Count (LIWC)—a program that tabulates word frequencies. We compare LIWC to a machine learning (ML) language model on the task of predicting grandiose narcissism (valid N = 471).We use the ML model discussed in Cutler and Kulis and formulate it as an extension of LIWC. With a strict validation scheme, the LIWC prediction was not more accurate than chance. The ML representation did moderately better ( R 2 = .043). This indicates that the ML model was able to preserve personality information where LIWC failed to do so, suggesting that precautions are warranted for social-personality research that relies solely on LIWC
Cognitive psychology · Narcissism · Natural language processing · Personality · Computer Science · Genetic Associations and Epidemiology · Personality Disorders and Psychopathology · Personality Traits and Psychology · Psychology · Social Psychology
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| Obras citantes distintas | 4 |
|---|---|
| Citações por ano | 1,33 |
| Intervalo de citações | 2023 - 2025 (3) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 4 |