Cornell University
Library
Cornell UniversityLibrary

eCommons

Help
Log In(current)
  1. Home
  2. Cornell SC Johnson College of Business
  3. Cornell Peter and Stephanie Nolan School of Hotel Administration
  4. Centers and Institutes
  5. The Center for Hospitality Research (CHR)
  6. Center for Hospitality Research Reports
  7. What Guests Really Think of Your Hotel: Text Analytics of Online Customer Reviews

What Guests Really Think of Your Hotel: Text Analytics of Online Customer Reviews

File(s)
Han_2016_What_guest_really_think.pdf (273.38 KB)
Permanent Link(s)
https://hdl.handle.net/1813/71232
Collections
Center for Hospitality Research Reports
Author
Han, Hyun Jeong “Spring”
Mankad, Shawn
Gavirneni, Nagesh
Verma, Rohit
Abstract

Hotel ratings do not tell the full story of how guests view a hotel, according to an analysis of the text of 5,830 reviews covering 57 hotels in Moscow, Russia. The study found, for instance, that negative comments have a heavier weight in a guest’s rating of a hotel than do positive comments. This uneven weighting means that a simple average of positive and negative scores may not provide a clear view of guests’ opinion of the hotel. This finding also underlines the importance of consistency, because guests’ bad feelings from poor service generally will submerge their favorable feelings from good service. The study applied a regression analysis to the relationships of 18,106 distinct terms relating to five specific attributes—amenities, experience, location, transactions, and value. Reviews for different hotel tiers gave varying weights to those attributes. For instance, the guest’s experience was mentioned more commonly in reviews of high-tier hotels, while amenities and location came up more frequently for motels in the middle tier compared to hotels in other tiers. Guests at the lower tier properties wrote more commonly about transactions and value than those staying at hotels in the middle and high tiers. One particularly noticeable feature of the reviews is that ratings sank when guests wrote lengthy reviews that focused tightly on a limited number of hotel attributes, while relatively briefer reviews that took a wider view of the hotel generally had higher ratings. The study also found that guests write more about value and transactions when they are dissatisfied. Thus, text analytics can point to specific steps managers can take to improve guests’ assessments and their hotels’ ratings.

Date Issued
2016-02-09
Keywords
online reviews
•
data mining
•
guest reviews
•
hotel ratings
•
guest feedback
Rights
Required Publisher Statement: © Cornell University. This report may not be reproduced or distributed without the express permission of the publisher.
Type
article

Site Statistics | Help

About eCommons | Policies | Terms of use | Contact Us

copyright © 2002-2026 Cornell University Library | Privacy | Web Accessibility Assistance