惊喜
旅游
心理学
厌恶
幸福
娱乐
情绪分类
国内旅游
面部表情
愤怒
社会化媒体
情绪分析
夸张
在线和离线
社会心理学
旅游地理学
政治学
计算机科学
人工智能
沟通
精神科
法学
作者
Zhonghao Zhang,Sunweiyu Huang,Siyu Zhang,Xiang Liu,Wei Jiang,Zihao Zheng,Junjun Zhi,Yi Long
标识
DOI:10.1080/10941665.2023.2293786
摘要
Online texts and images have become an important data source for investigating tourism emotion. However, tourism emotion extracted from online data cannot reflect the emotions in the real world. Few scholarly attempts have focused on the complex biases in tourism emotion based on online data. By comparing online and offline emotion, this study quantified biases in tourism emotion and explored patterns among biases. Facial expressions and texts within Disney Resort were collected. Based on facial expression recognition and text mining, several indices were proposed to measure tourism emotion and biases. Our results reveal that tourists tend to share stronger happiness, increased anger in commerce areas and exaggerated disgust in waiting areas. In addition, males show "surprise-suppress"; while females show "surprise-exaggeration" in recreation areas. Our research can help scholars reexamine previous conclusions based on online tourism emotion and provides a theoretical basis for improving the quality of online tourism emotion.
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