Research on text analysis has demonstrated that texts can reveal various characteristics of individuals, such as personality, preferences, or future behavior. However, despite its numerous applications in other fields, text analysis has received very little attention in the field of empirical aesthetics. This study aimed to analyze texts written about artworks and examine the relationship between certain demographic factors and the use of words, using a novel framework for computer-based text analysis based on neural embedding. Participants provided textual descriptions of paintings from various genres and eras, along with demographic information such as gender, age, income, frequency of museum visits, and knowledge of artworks. The results revealed a significant relationship between some demographic factors and word usage, while also highlighting the usefulness of the proposed framework.
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