Dados Bibliográficos

AUTOR(ES) James W. Pennebaker , Yi-Tai Seih , Susanne Beier
AFILIAÇÃO(ÕES) The University of Texas at Austin, University of Heidelberg, Heidelberg, Germany
ANO 2017
TIPO Artigo
PERIÓDICO Journal of Language and Social Psychology
ISSN 0261-927X
E-ISSN 1552-6526
EDITORA Annual Reviews (United States)
DOI 10.1177/0261927x16657855
CITAÇÕES 2
ADICIONADO EM 2025-08-18
MD5 a46ad59e2231a2f3fc642282d5567449

Resumo

The linguistic category model (LCM) seeks to understand social psychological processes through the lens of language use. Its original development required human judges to analyze natural language to understand how people assess actions, states, and traits. The current project sought to computerize the LCM assessment based on an idea of language abstraction with a previously published data set. In the study, a computerized LCM analysis method was built using an LCM verb dictionary and a part-of-speech tagging program that identified relevant adjectives and nouns. This computerized method compared open-ended texts written in first-person and third-person perspectives from 130 college students. Consistent with construal-level theory, third-person writing resulted in higher levels of abstraction than first-person writing. Implications of relying on an automated LCM method are discussed.

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