Topic modelling and hotel rating prediction based on customer review in Indonesia

Yunanto Putranto, Bagus Sartono and Anik Djuraidah

International Journal of Management and Decision Making, 2021, vol. 20, issue 3, 282-307

Abstract: The growth of the tourism sector and the use of hotel online booking platforms lead to the creation of textual data sources in the form of customer review. Motivation of this study is to add value to the customer review, using more than 50,000 samples taken from 510 hotels across Indonesia. First added value is understanding most talked topics by hotel customers. Using topic model latent Dirichlet allocation (LDA), this study revealed that services, price/food, facility, comfort and location are the most talked topics. Secondly, numerical hotel rating is derived from textual data using ridge regression. In addition, regression coefficient indicates the sentiment of each word in the customer review. Finally, the output of this study is expected to be useful for customers in assessing hotel service quality and in making booking decisions, and for hotel operators to get additional input during management decision making.

Keywords: topic model; latent Dirichlet allocation; LDA; ridge regression; Indonesia. (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=116028 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmdma:v:20:y:2021:i:3:p:282-307

Access Statistics for this article

More articles in International Journal of Management and Decision Making from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().