LEARNING AND EMOTIONAL-AFFECTIVE MUSEUM EXPERIENCE VIA TEXTUAL SENTIMENT ANALYSIS

Iana Fominska, Umberto Bilotti, Stefano Di Tore, Gerardo Iovane

Abstract


In this paper we propose a model to enhance emotional learning in museums by detecting visitor emotions through Google Forms surveys on virtual exhibits. We utilize sentiment analysis and physiological measures to understand emotional states, aiming to improve classification accuracy through multimodal analysis. Additionally, text analysis aids sentiment assessment, emphasizing the crucial role of feedback in visitor engagement.


Keywords


Emotional Learning, Museum Experience, Textual Sentiment Analysis, Visitor Engagement, Virtual Exhibit.

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References


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DOI: https://doi.org/10.32043/gsd.v8i2.1099

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