Under growing pressure to demonstrate its societal value, marketing research has the opportunity to focus more on increasing our understanding of consumer happiness. The present research uses topic modeling to interpret and categorize comments from Yelp.com reviews about travel dimensions. In addition, sentiment analysis was used to capture the number of positive and negative words in each review. The data analysis is used to extract and explore the dominant consumer emotions surrounding travel. This research contributes to the practice of marketing and society more broadly by providing an understanding of how memorable experiences are shaped in the travel context and also by demonstrating how machine learning (text mining) can help better understand concepts relating to consumer happiness and well-being.

在证明其社会价值的压力越来越大的情况下，营销研究有机会更多地关注提高我们对消费者幸福感的理解。本研究使用主题建模来解释和分类来自 Yelp.com 评论中关于旅行维度的评论。此外，使用情感分析来捕获每条评论中正面和负面词的数量。数据分析用于提取和探索围绕旅游的主要消费者情绪。这项研究通过了解旅行环境中令人难忘的体验是如何形成的，以及展示机器学习（文本挖掘）如何帮助更好地理解与消费者幸福和福祉相关的概念，为更广泛的营销和社会实践做出贡献.