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

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.

[1]  Shahriar Akter,et al.  Big data analytics in E-commerce: a systematic review and agenda for future research , 2016, Electronic Markets.

[2]  Jerome Couturier,et al.  Big data analytics capabilities and knowledge management: impact on firm performance , 2019, Management Decision.

[3]  Barbara Neuhofer,et al.  The influence of social media on the consumers’ hotel decision journey , 2017 .

[4]  Sohyeon Kim,et al.  Network text analysis of medical tourism in newspapers using text mining: The South Korea case , 2019, Tourism Management Perspectives.

[5]  Eleonora Pantano,et al.  Making sense of consumers’ tweets , 2019, International Journal of Retail & Distribution Management.

[6]  S. Becken,et al.  Sentiment Analysis in Tourism: Capitalizing on Big Data , 2019 .

[7]  Terry Anthony Byrd,et al.  Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations , 2018 .

[8]  Gurinder Singh,et al.  Comparison between Multinomial and Bernoulli Naïve Bayes for Text Classification , 2019, 2019 International Conference on Automation, Computational and Technology Management (ICACTM).

[9]  Juan Luis Nicolau,et al.  Asymmetric effects of online consumer reviews , 2015 .

[10]  Xun Xu,et al.  Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews , 2019, International Journal of Hospitality Management.

[11]  Giustina Secundo,et al.  Creating value from Social Big Data: Implications for Smart Tourism Destinations , 2017, Inf. Process. Manag..

[12]  Q. Ye,et al.  Analysis of the Perceived Value of Online Tourism Reviews: Influence of Readability and Reviewer Characteristics , 2016 .

[13]  G. Viglia,et al.  Technological disruptions in services: lessons from tourism and hospitality , 2019, Journal of Service Management.

[14]  Chun-Hung Chen,et al.  Social media analytics: Extracting and visualizing Hilton hotel ratings and reviews from TripAdvisor , 2017, Int. J. Inf. Manag..

[15]  Mohamed Cheriet,et al.  A Human-Guided Machine Learning Approach for 5G Smart Tourism IoT , 2020, Electronics.

[16]  F. Okumus,et al.  Understanding Satisfied and Dissatisfied Hotel Customers: Text Mining of Online Hotel Reviews , 2016 .

[17]  M. Rothenberger,et al.  The path to the Hotel of Things: Internet of Things and Big Data converging in hospitality , 2019, Journal of Hospitality and Tourism Technology.

[18]  Stuart J. Barnes,et al.  Understanding the Impact of Online Reviews on Hotel Performance , 2017 .

[19]  Kuanchin Chen,et al.  Predicting hotel review helpfulness: The impact of review visibility, and interaction between hotel stars and review ratings , 2016, Int. J. Inf. Manag..

[20]  Wu He,et al.  Application of social media analytics: a case of analyzing online hotel reviews , 2017, Online Inf. Rev..

[21]  Zheng Xiang,et al.  A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism , 2017 .

[22]  Neil Y. Yen,et al.  User sentiment analysis based on social network information and its application in consumer reconstruction intention , 2019, Comput. Hum. Behav..

[23]  John Qi Dong,et al.  Business value of big data analytics: A systems-theoretic approach and empirical test , 2020, Inf. Manag..

[24]  Albert A. Barreda,et al.  The impact of social media activities on brand image and emotional attachment , 2020 .

[25]  Marcello M. Mariani.  Big Data and analytics in tourism and hospitality: a perspective article , 2019, Tourism Review.

[26]  Mahmoud A. M. Albreem,et al.  A comprehensive study on the role of advanced technologies in 5G based smart hospital , 2021 .

[27]  Panchapakesan Padma,et al.  Guest satisfaction & dissatisfaction in luxury hotels: An application of big data , 2020 .

[28]  Sérgio Moro,et al.  Can we trace back hotel online reviews' characteristics using gamification features? , 2019, Int. J. Inf. Manag..

[29]  Dac-Nhuong Le,et al.  PTS-PAPR Reduction Technique for 5G Advanced Waveforms Using BFO Algorithm , 2021 .