Hotel customer segmentation and sentiment analysis through online reviews: an analysis of selected European markets

被引:10
|
作者
Oliveira, Anderson S. [1 ]
Renda, Ana, I [1 ,2 ,3 ]
Correia, Marisol B. [1 ,2 ,3 ,4 ]
Antonio, Nuno [2 ,5 ]
机构
[1] Univ Algarve, Sch Management Hospitality & Tourism ESGHT, Faro, Portugal
[2] Ctr Tourism Res Dev & Innovat CiTUR, Leiria, Portugal
[3] Ctr Tourism Sustainabil & Well Being CinTurs, Faro, Portugal
[4] Univ Lisbon, Inst Super Tecn, CEG IST, Lisbon, Portugal
[5] Univ Nova Lisboa, NOVA Informat Management Sch NOVA IMS, Lisbon, Portugal
关键词
Online reviews; data mining; sentiment analysis; Tripadvisor; hotel management; TEXTUAL REVIEWS; SATISFACTION; IMPACT; HOSPITALITY; PREFERENCES;
D O I
10.18089/tms.2022.180103
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study aims to verify how distinct markets evaluate hotels in the Algarve through the analysis of online reviews, in order to identify if satisfaction and dissatisfaction attributes are similar among some of the main markets of overnight stay tourists in the region. Online reviews of hotels in the Algarve, written in English, French as well as Portuguese and posted on Tripadvisor by British, French and Portuguese residents from January 2019 to December 2019 are analysed. After the analysis of 8,596 online textual reviews, the results demonstrated that not only satisfaction and dissatisfaction rates towards hotel attributes differ according to the language, but also that customers from different countries place dissimilar emphasis on hotel attributes. Besides extending the current research on the use of online reviews, the findings of this study also assist hoteliers to identify improvement opportunities. Although many studies on marketing segmentation through data mining have been conducted, this paper analyses the customer satisfaction of relevant tourist markets and suggests up-todate practical implications for hoteliers.
引用
收藏
页码:29 / 40
页数:12
相关论文
共 50 条
  • [31] Forecasting Hotel Room Occupancy Using Long Short-Term Memory Networks with Sentiment Analysis and Scores of Customer Online Reviews
    Chang, Yu-Ming
    Chen, Chieh-Huang
    Lai, Jung-Pin
    Lin, Ying-Lei
    Pai, Ping-Feng
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (21):
  • [32] Customer Satisfaction Attribution Analysis of Hotel Online Reviews Based on Qualitative Research Methods
    Ye, Pinghao
    Yu, Bin
    [J]. ICEBT 2018: PROCEEDINGS OF THE 2018 2ND INTERNATIONAL CONFERENCE ON E-EDUCATION, E-BUSINESS AND E-TECHNOLOGY, 2018, : 93 - 98
  • [33] INFORMATION EXTRACTION AND SENTIMENT ANALYSIS OF HOTEL REVIEWS IN CROATIA
    Suman, Sabrina
    Vignjevic, Milorad
    Car, Tomislav
    [J]. ZBORNIK VELEUCILISTA U RIJECI-JOURNAL OF THE POLYTECHNICS OF RIJEKA, 2023, 11 (01): : 69 - 89
  • [34] Topic-based sentiment analysis of hotel reviews
    Gharzouli, Mohamed
    Hamama, Aimen Khalil
    Khattabi, Zakaria
    [J]. CURRENT ISSUES IN TOURISM, 2022, 25 (09) : 1368 - 1375
  • [35] Multi-Language Sentiment Analysis for Hotel Reviews
    Sodanil, Maleerat
    [J]. 2016 INTERNATIONAL CONFERENCE ON MEASUREMENT INSTRUMENTATION AND ELECTRONICS (ICMIE 2016), 2016, 75
  • [36] Aspect-Level Sentiment Analysis on Hotel Reviews
    Panigrahi, Nibedita
    Asha, T.
    [J]. COMPUTATIONAL INTELLIGENCE IN DATA MINING, 2019, 711 : 379 - 389
  • [37] A Framework for Sentiment Analysis with Opinion Mining of Hotel Reviews
    Zvarevashe, Kudakwashe
    Olugbara, Oludayo O.
    [J]. 2018 CONFERENCE ON INFORMATION COMMUNICATIONS TECHNOLOGY AND SOCIETY (ICTAS), 2018,
  • [38] Sentiment Analysis for Hotel Reviews: A Systematic Literature Review
    Ameur, Asma
    Hamdi, Sana
    Ben Yahia, Sadok
    [J]. ACM COMPUTING SURVEYS, 2024, 56 (02)
  • [39] Exploring Bidirectional Performance of Hotel Attributes through Online Reviews Based on Sentiment Analysis and Kano-IPA Model
    Chen, Yanyan
    Zhong, Yumei
    Yu, Sumin
    Xiao, Yan
    Chen, Sining
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (02):
  • [40] Exploring eWOM in online customer reviews: Sentiment analysis at a fine-grained level
    Sun, Qing
    Niu, Jianwei
    Yao, Zhong
    Yan, Hao
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2019, 81 : 68 - 78