Understanding Destination Image in UGC: A Lexicon Approach

This study hastaken a pioneer position to apply semantic analysis to examine destination image through  user-generated blog entries. Based on semantic rules, statistical analysis and co-occurrence analysis, this  paper has analyzed blog entries generated by Chinese domestic visitorson the social media platform. A total  of 3,160 valid reviews have been analyzed to compute semantic scores, explored the relationship between  destination component and semantic scores and, investigated the features of positive and negative blog  entries respectively. The findings have shownthat several dimensions of destination image are presented in  the social media with each carrying different weight. It has also been proved that there is also a strong  relationship between destination image and semantic scores. Prominent different clusters have been  discovered in positive and negative comments, indicating different aspects of the destination are recognized  by tourists. This study has embraced the challenges of converting the large volume of unstructured data into  structure data for destination marketing and management. This work has also progressed in combining both  semantic rules and statistical analysis.

 Keywords: sentiment analysis, user-generated-content, destination image; big data; lexicon approach.