Predicting A New Hotel Rating System by Analysing UGC Content from Tripadvisor: Machine Learning Application to Analyse Service Robots Influence

被引：10

作者：

Calero-Sanz, Jorge ^{[1
,2
,3
]}

Orea-Giner, Alicia ^{[3
,4
,5
,6
]}

Villace-Molinero, Teresa ^{[3
,5
,6
]}

Munoz-Mazon, Ana ^{[3
,5
,6
]}

Fuentes-Moraleda, Laura ^{[3
,5
,6
]}

机构：

[1] Rey Juan Carlos Univ, Signal & Commun Theory & Telemat Syst & Comp, Madrid, Spain

[2] Tech Univ Madrid, Dept Appl Math & Stat, EIAE, Madrid, Spain

[3] Rey Juan Carlos Univ, High Performance Res Grp OPENINNOVA, Madrid, Spain

[4] Univ Paris 1 Pantheon Sorbonne, EIREST, Paris, France

[5] Rey Juan Carlos Univ, Business Econ, Madrid, Spain

[6] Rey Juan Carlos Univ, Ctr Univ Estudios Turist, Madrid, Spain

来源：

3RD INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING | 2022年 / 200卷

关键词：

robot typology; traveler; TripAdvisor Rating; Machine Learning; ONLINE REVIEWS; BIG DATA; TOURISM; HOSPITALITY; EXPERIENCE;

D O I：

10.1016/j.procs.2022.01.307

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Industry 4.0 tools permit computerized creation measures, and Artificial Intelligence (AI) approaches are pivotal in investigating the travel industry. Applying these devices to decipher User Generated Content (UGC) is fundamental to understand better client's necessities, opinions, and assumptions regarding tourism services. Through this research, an exploratory analysis of results is developed through Machine Learning Models to understand better the role played by robot and traveler typologies on the rating given to hotels considering TripAdvisor reviews of 74 hotels. The purpose of this exploratory research is to develop a methodology focused on analyzing online reviews related to service robots in hotels using Machine Learning techniques to train the data collected from TripAdvisor. Preliminary results show a link between the hotel rating given in TripAdvisor and the robot typology implemented in hotels. (C) 2022 The Authors. Published by Elsevier B.V.

引用

页码：1078 / 1083

页数：6