Enhancing hospitality sentiment reviews analysis performance using SVM N-grams method

Enrico Laoh, Isti Surjandari, Nadhila Idzni Prabaningtyas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Sentiment analysis or opinion mining is an analysis conducted to derive meaningful information or sentiments contained in an opinion. The use of sentiment analysis has spread in various fields, also exists in the tourism sector. Many tourists are actively reading and writing reviews on travel websites or travel platforms. Whereas in the review information contained useful information for the company or hotel manager, considering that the hospitality industry is very competitive. This analysis produces knowledge about sentiment from the review text data using approaches of n-grams to increase the level of accuracy according to the literature proven. This research uses SVM as a review classification method with positive and negative sentiment. The results of this research indicate an average level of accuracy of 94% which is greater than the level of accuracy in previous research using the same data. In addition, this research shows that the use of SVM as a classification model produces a higher level of accuracy than the Recursive Neural Tensor Network (RNTN).

Original languageEnglish
Title of host publication2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728119410
DOIs
Publication statusPublished - Jul 2019
Event16th International Conference on Service Systems and Service Management, ICSSSM 2019 - Shenzhen, China
Duration: 13 Jul 201915 Jul 2019

Publication series

Name2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019

Conference

Conference16th International Conference on Service Systems and Service Management, ICSSSM 2019
Country/TerritoryChina
CityShenzhen
Period13/07/1915/07/19

Keywords

  • Hospitality
  • N-Grams
  • Sentiment Analysis
  • Support Vector Machine (SVM)
  • Tourism

Fingerprint

Dive into the research topics of 'Enhancing hospitality sentiment reviews analysis performance using SVM N-grams method'. Together they form a unique fingerprint.

Cite this