Dance and social engagement in motion: An Emotional Text Mining analysis

Abstract

This study explores the intersection between emotions, collective action and artistic expression, highlighting the role of dance as expressive language through which affective experiences are socially and politically articulated. In particular, it seeks to understand how performative art, particularly dance, is communicated and perceived as a means of political and social engagement. The research combines sociological theory with computational text analysis, adopting an Emotional Text Mining methodology implemented via T-Lab software. The analysis focuses on a corpus of 50 performance synopses produced by three Italian art collectives (De Anima Movement, Spellbound Contemporary Ballet and Compagnia Zappalà Danza) between January 1, 2023, and March 31, 2025. Using a hybrid clustering approach (Ward + K-Means), the study identifies recurrent emotional themes and symbolic patterns in artistic discourse. Semantic saturation and thematic density guided the validity of results, while statistical metrics confirmed corpus adequacy. Findings confirm that embodied artistic practices are communicated and perceived by these activists as a means of political and social mobilization. They are not viewed only as aesthetic expressions, but as emotional catalysts, capable of instigating a change, transforming individual affect into shared meaning.