An improved model for sentiment analysis on luxury hotel review

Abstract

This paper proposes a heuristic model for sentiment analysis on luxury hotel reviews to analyze and explore marketin g insights from attitudes and emotions expressed in reviews. We make several significant contributions to visual and multimedia analytics. This research will develop the practical application of visual and multimedia analytics as the research foundation is based on information analytics, geospatial analytics, statistical analytics and data management. Large amounts of data are generated by hotel customers on the Internet, which provides a good opportunity for managers and analysts to explore the hidden information. The analysis of luxury hotels involves different types of data, including real-world scale data, high-dimensional data and geospatial data. The diversity of data increases the difficulty of processing computational visual analytics. It leads to that some classical classification methods, which cost too much time and have high requirements for hardware, are excluded. The goa l is to achieve a compromis e between performance and cost. An experiment of this model is operated using data extracted from Booking.com. The entire framework of this experiment includes data collection, data preprocessing, feature engineering consisting of TF-IDF and Doc2Vec based feature generation and feature selection, Random Forest class ification, data analysis, and data visualization. The whole process combines statistical analysis, review sentiment analysis, and visual analysis to make full use of this dataset and gain more decision-making information to improve luxury hotels' service quality. Compared with simple sentiment analysis, this integrated analytics in social media is expected to be used in practice to gain more insights. The result shows that luxury hotels should focus on staff training, cleanness of rooms and location choice to improve customer satisfaction. The sentiment distribution shows that scores are consistent with the emotion they show in reviews. Hotels in Spain have a much better average score than hotels in the other five countries. In the experiment, the sentiment analysis model is evaluated by ROC and PR curve. It is proved that this model performs well. Twenty most essential features have been listed for future adjustments to the model.

Social media and luxury: A systematic literature review

“…Blasi et al, 2020;Chen et al, 2021a), as well as user reviews and subsequent response strategies by management on related platforms (e.g. Chang et al, 2020;Jang & Moutinho, 2019;Schuckert et al, 2019), particularly in the hospitality industry.…”

Impact of Luxury Hotel Customer Experience on Brand Love and Customer Citizenship Behavior

“…As the experience economy is becoming an industry-wide core component, luxury hotels as a part of the experience economy attempt to provide customers with a superior geographical location, 24-hour room service, an expansive space, expensive facilities, high-quality food, elegant aesthetics, privacy, security, and highly customized services [1,2]. With the popularity of luxury hotels in the hotel industry, exquisite decoration and upscale facilities have become the standard in every luxury hotel; therefore, customers have begun to pay attention to details and demand higher service and support facilities [3]. Thus, marketers and general managers of luxury hotels must attach great importance to the customer evaluations of service experiences provided by hotels and the subsequent behaviors via customers' perceptions of service experiential value regarding their stay in a luxury hotel.…”

Exploring E-Commerce Product Experience Based on Fusion Sentiment Analysis Method

“…Correspondingly, Almjawel et al [27] tried to conduct comprehensible sentiment analysis of online book reviews collected from Amazon to assist users in making efficient purchasing decisions. With respect to services, Chang et al [28] explored the service quality of the hotel from the standpoint of consumers. By analyzing the attitudes and emotions conveyed in customer comments, they found that professional services and clean rooms have a positive effect on improving customer satisfaction.…”