One Destination Two Images: A Social Media Text Analytics Approach to Uncovering Tourist Perceptions of Beijing
Shu-Tai Wang, Ping-Ho Ting

With the development of digital technology, there has been an exponential growth of traveler generated content, which forms part of big data essential for the development of smart tourism destination. Yet there is limited research using the latest analytical tools to evaluate destination image from the freely available data in social media. This study aims to fill this gap by applying a machine learning based text analytical tool, CKIP (Chinese Knowledge and Information Processing) to uncover tourist perceptions of Beijing. Textual data extracted from major online travel blogs were examined to compare the similarities and differences of image as perceived between mainland Chinese and Taiwanese tourists. The results indicated that the two groups shared great interests in sightseeing and dining, yet surprisingly Taiwanese showed stronger positive affection towards Beijing. This study also demonstrates that CKIP can be an useful tool to support tourism researchers from western languages background when analyzing the Chinese textual data that are increasingly present in popular social media for interesting insights in destination management and marketing.

Full Text: PDF     DOI: 10.15640/jthm.v8n1a4