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A Multi-Method Approach to Analyzing Museum Exhibition Experiences: Topic Modeling and Image Analysis of Instagram Data

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2025, 30(10), pp.91~103
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : September 5, 2025
  • Accepted : September 29, 2025
  • Published : October 31, 2025

Sol-Mi Moon 1 Bo-A Rhee 1

1중앙대학교

Accredited

ABSTRACT

This study represents a convergent research methodology integrating arts management and technology, analyzing visitor experiences of 《Blooming Hwarot: Bridal Robes of the Joseon Royal Court》through topic modeling and image recognition. Text mining of Instagram posts with TF-IDF and LDA was applied to identify both objective information (exhibition title, theme, location) and subjective responses, including storytelling on restoration, curatorial elements, and expressions of admiration and beauty. The LDA results show that visitors emphasize the cultural value and conservation of the hwarot. Image analysis, using Google Cloud Vision API and Word2Vec, extracts 39,335 labels, categorized into eleven thematic groups. Fashion groups have the highest label frequencies, while Exhibition accounts for the largest proportion across the dataset.

Citation status

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