Customers’ metaverse service encounter perceptions: sentiment analysis and topic modeling
S. Jerrin Issac Sam, K. Mohamed Jasim, M. Babu
Abstract
Using machine learning, we examined customers’ opinions about the metaverse in the hospitality industry (encompassing hotels, restaurant, gaming, virtual events, tours and travel). A total of 8,855 tweets were collected from Twitter (now called X), and machine learning algorithms such as sentiment analysis and topic modeling were performed using Python libraries to capture the important topics related to metaverse applications. Nearly two thirds of the collected tweets (60.9%) contained a mostly positive general sentiment toward the use of the metaverse. Six important topics emerged from the topic modeling: gaming, virtual events, virtual sightseeing, travel, business and blockchain. Despite numerous studies on the proper integration of the metaverse, VR and AR, to the best of our knowledge, this is one of the first studies conducted to determine the customer experience of the metaverse in the hospitality industry using social media data.