Love, Language, and Linear Algebra: Linguistic Modeling of Personality and Mate Preference

Abstract

This study utilized Latent Semantic Analysis to determine whether similarities in personality predicted similarities in responses to a romantic writing prompt (Landauer & Dumais, 1997). From participants’ writing samples, we calculated thematic cosines (a measure of relatedness) between each male and female participant. Participants also completed the Big Five Personality Questionnaire Short Form (Morizet, 2014). Extraversion, agreeableness, and conscientiousness were related to cosines, which suggested small-medium relationships from personality traits to written responses. This relationship was consistent with previous studies; therefore, Latent Semantic Analysis may be useful in quantifying mate preference, especially when alongside traditional survey methods. We conclude with a discussion of the compatibility of ordinal measures (survey data) and continuous measures in examining complex phenomena in the Behavioral Sciences

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