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Влияние социально-демографических факторов на эмоциональное восприятие текста цифровой коммуникации: опыт экспериментального исследования
Emotional interpretation of digital texts requires the reconstruction of the author’s intent. According to Activity Theory, emotions are shaped by historical and cultural factors rather than human biology. Using the Geneva Emotion Wheel model, the authors studied responses to a digital communication text in order to measure the convergence between attributed emotions (those the reader ascribes to the author) and the reader’s own emotional response. The survey involved 106 participants with diverse social and demographic profiles. The questionnaire was based on the premise that the semantic perception of a text involves both the author and the reader. It aimed to analyze the effect of gender and age on emotional distance, attribution, and response. A metric based on the number of distinct tokens made it possible to formalize the distance between attributed and experienced emotions. The number of responses showing emotion convergence (50%) equaled the number of responses without matches (50%). Partial convergence (28.4%) proved to be more frequent than full convergence (21.6%). Female and younger respondents demonstrated a larger emotional distance between the image of the author and the reader’s response. However, response varied significantly within each social group. The impact of gender and age on the convergence between the attributed and felt emotions proved highly variable, depending on the respondent’s own cultural experience.