The management of museums is gradually shifting towards data-driven and digital governance approaches to enhance visitor relationship management and improve both operational efficiency and user experience. An essential part of effective visitor relationship management is the analysis of visitor data. In addition to data from physical visits to exhibitions, such as visitor numbers and survey responses, online discussions by visitors are increasingly valued. This study conducts empirical research using opinion mining and sentiment analysis techniques to analyze online discussions about museums. After analyzing the data from April to June 2023, which includes discussions from 1058 websites and 133,963 forum posts, the study offers recommendations for the future management of museums. The analyses include trend analysis of discussion volume, sentiment analysis, media analysis of discussion volume, and content keyword analysis.

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Applying Opinion Mining and Social Volume Analysis for Enhanced Visitor Relationship Management in a Museum: An Empirical Study

  • I-Hsien Ting,
  • Mei-Yun Hsu,
  • Chia-Sung Yen,
  • Chian-Hsueng Chao

摘要

The management of museums is gradually shifting towards data-driven and digital governance approaches to enhance visitor relationship management and improve both operational efficiency and user experience. An essential part of effective visitor relationship management is the analysis of visitor data. In addition to data from physical visits to exhibitions, such as visitor numbers and survey responses, online discussions by visitors are increasingly valued. This study conducts empirical research using opinion mining and sentiment analysis techniques to analyze online discussions about museums. After analyzing the data from April to June 2023, which includes discussions from 1058 websites and 133,963 forum posts, the study offers recommendations for the future management of museums. The analyses include trend analysis of discussion volume, sentiment analysis, media analysis of discussion volume, and content keyword analysis.