The linguistic category model (LCM) tries to understand social psychological processes via the lens of language use. Its original development required human judges to explore natural language to comprehend 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 formerly published data set. In the inquiry, a computerized LCM analysis method was built employing an LCM verb dictionary and a part-of-speech tagging program that distinguished 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 depending on an automated LCM method are debated.