Emotion Analysis of Tourists Based on Domain Ontology

Abstract

The big data of tourism has exploded with the rapid development of social media, providing a new data source for the emotion analysis of tourism. Based on online comments, this paper proposes an emotion analysis model that combines tourism domain ontology and semantic-based method to mine the fine-grained emotion of tourists and designs specific formulas to quantify the emotion of tourists. Finally, the Palace Museum is used as an example to verify the validity of the model. The analysis results show that: 1) Tourists pay more attention to the attributes such as "scenery", "tourist flow", "ticket", etc. in their travel activities. 2) The emotional score of the attributes such as "lodging environment", "scenery", "culture", "environment quality", etc. are higher, but the attributes such as "safety", "tourist flow", "toilet" and cost-related attributes are lower. The main reasons are: "low security", "massive tourists", "less and small toilets" and "high costs". 3) Due to the excessive number of tourists during the holiday, which leads poor travel experience to the tourists, the emotional score of tourists are lower in the 5th, 7th, 8th and 10th months. The analysis results can provide reference for tourists' travel decisions and the development and optimization of tourism.