Capitalizing on big data and revolutionary 5G technology: Extracting and visualizing ratings and reviews of global chain hotels

Abstract

This paper aims to use machine learning (ML) algorithm for natural language pre-processing (NLP), text mining (TM), and sentiment analysis (SA) techniques to analyze and examine 45,500 online reviews of customers of 50 global chain hotels from different online review sites. Furthermore, the paper addresses the new business value and experiences that the revolutionary 5G technology can bring to the hotel industry. The research findings revealed that the general review star rating corresponds with the opinion (sentiment) scores for the title and the full substance of the online reviews. The case study’s contextual analysis also uncovered that both fulfilled and disappointed customers have a frequent inclination for five categories: food, stay, rooms, service, and staff. This study contributes both theoretically and practically to the multidisciplinary domains of computer science, information systems, and tourism and discovers hidden patterns in data using visual analytics techniques.