Tourists Perception in Bali Using Social Media and Online Media Sentiment Analysis

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

Abstract

Indonesian tourism is one of the biggest contributors to the country's foreign income. In 2015 foreign income from the tourism sector was 12.23 billion and it is projected that in 2020 will contribute foreign income of 20 billion. Technological advances have fundamentally changed how information is produced and used for many things including in the tourism sector. Tourism Industry relies on feedback from its customers. In the tourism industry, customer experience is important for the development and reputation of the industry. New approaches to measure the level of customer satisfaction and perceptions of tourists through sentiment analysis are needed. In this study the problem that will be of concern is how to utilize sentiment analysis to determine the perceptions of tourists regarding 3A (attractions, amenities and accessibility) in tourism destinations, using the NLP (Natural Language Processing) text mining method to develop strategies for developing tourist destinations and increasing the number of tourists especially in Bali.

Original languageEnglish
Title of host publicationICETAS 2019 - 2019 6th IEEE International Conference on Engineering, Technologies and Applied Sciences
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728140827
DOIs
Publication statusPublished - Dec 2019
Event6th IEEE International Conference on Engineering, Technologies and Applied Sciences, ICETAS 2019 - Kuala Lumpur, Malaysia
Duration: 20 Dec 201921 Dec 2019

Publication series

NameICETAS 2019 - 2019 6th IEEE International Conference on Engineering, Technologies and Applied Sciences

Conference

Conference6th IEEE International Conference on Engineering, Technologies and Applied Sciences, ICETAS 2019
CountryMalaysia
CityKuala Lumpur
Period20/12/1921/12/19

Keywords

  • 3A
  • NLP
  • sentiment analysis
  • text mining
  • tourism

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