Parallel Session 3, MICE Track: Toward Unsupervised Machine Learning Technique to Discover the Key Topics Influence Exhibition Visitor Engagement in Social Media: A Case Study from Taiwan
Location
Classroom 209
Start Date
13-12-2017 2:00 PM
End Date
13-12-2017 2:25 PM
Description
Unsupervised machine learning of text mining in social media has become a new research area in the past decade. Topic modelling is a probabilistic generative model that has been used in the field of computer science and bioinformatics. This pioneer study utilized topic modelling in unsupervised machine learning technic to analyze the contemporary exhibition visitor engagement in social media Facebook fan page. Latent Dirichlet Allocation (LDA) result supported that the visitors were highly concerned with gamification activities for an incentive prize both to create involvement and to enhance exhibition experience. The results visualization provide a professional exhibition organizer (PEO) with accurate information in developing successful E-WOM marketing strategies in social media or an exhibition management design for promoting successful exhibition visitor engagements in real time.
Parallel Session 3, MICE Track: Toward Unsupervised Machine Learning Technique to Discover the Key Topics Influence Exhibition Visitor Engagement in Social Media: A Case Study from Taiwan
Classroom 209
Unsupervised machine learning of text mining in social media has become a new research area in the past decade. Topic modelling is a probabilistic generative model that has been used in the field of computer science and bioinformatics. This pioneer study utilized topic modelling in unsupervised machine learning technic to analyze the contemporary exhibition visitor engagement in social media Facebook fan page. Latent Dirichlet Allocation (LDA) result supported that the visitors were highly concerned with gamification activities for an incentive prize both to create involvement and to enhance exhibition experience. The results visualization provide a professional exhibition organizer (PEO) with accurate information in developing successful E-WOM marketing strategies in social media or an exhibition management design for promoting successful exhibition visitor engagements in real time.
Accessibility Statement
This item was created or digitized prior to April 24, 2027, or is a reproduction of legacy media created before that date. It is preserved in its original, unmodified state specifically for research, reference, or historical recordkeeping. In accordance with the ADA Title II Final Rule, the University Libraries provides accessible versions of archival materials upon request. To request an accommodation for this item, please submit an accessibility request form.
