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Article citations


Guo, G. and Chan-Olmsted, S.M. (2015) Predictors of Social Television Viewing: How Perceived Program, Media, and Audience Characteristics Affect Social Engagement with Television Programming. Journal of Broadcasting & Electronic Media, 240-258.

has been cited by the following article:

  • TITLE: Social Media Sentimental Analysis in Exhibition’s Visitor Engagement Prediction

    AUTHORS: Tian-Shyug Lee, Ben-Chang Shia, Chung-Ling Huh

    KEYWORDS: Social Media, Text Mining, Sentimental Analysis, Engagement

    JOURNAL NAME: American Journal of Industrial and Business Management, Vol.6 No.3, March 31, 2016

    ABSTRACT: In the internet age, social media and mobile devices are the most important tools of communication and marketing in the exhibition and event industry. Only a limited research has explored exhibition visitors’ engagement and preference perception through social networking media. Our study explores relationship between Facebook fan pages and visitor engagements of the exhibitions. The study found that the number of visitors, Facebook fans like counts, comment counts, and emotional factors (sentiment polarity) have a significant positive correlation. On the other hand, numbers of visitor rapidly grow every year, but comment sentiment polarity of a positive emotion drops every year. This reduction is the warning sign that the exhibition management and marketing strategy need to be improved in order to continue to have a positive visitor engagement emotion. Our linear Discriminate Analysis (LDA) result found that visitors were highly concerned with gamification activities for an incentive prize both to create involvement and to enhance exhibition experience. Our finding also shows the relevance of both FB like counts and comments generated by social media in relation to the visitor engagement performance. This pioneer study utilized both text mining and sentimental analysis into the exhibition study, especially the area of Asian research.