Capitalizing on big data and revolutionary 5G technology: Extracting and visualizing ratings and reviews of global chain hotels
Loveleen Gaura, Anam Afaqa, Arun Solankib, Gurmeet Singhc, Shavneet Sharmac, Noor Zaman Jhanjhid, Hoang Thi Mye, Dac‐Nhuong Lef g✉
- aAmity International Business School, Amity University, Noida, Uttar Pradesh, India
- bGautam Buddha University, Greater Noida, Uttar Pradesh, India
- cThe University of the South Pacific (USP), Faculty of Business & Economics, Suva, Fiji
- dSchool of Computer Science and Engineering SCE, Taylor’s University, Malaysia
- eFaculty of Tourism, Haiphong University, Haiphong 180000, Viet Nam
- fInstitute of Research and Development, Duy Tan University, Danang 550000, Viet Nam
- gSchool of Computer Science, Duy Tan University, Danang 550000, Viet Nam
- ✉Corresponding author
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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.
TL;DRThis 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. (Semantic Scholar)