research-article

Mining Tourist's Perception toward Indonesia Tourism Destination Using Sentiment Analysis and Topic Modelling

Authors:

Riefvan Achmad MasruryAuthors Info & Claims

CCIOT '19: Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things

Pages 7 - 12

https://doi.org/10.1145/3361821.3361829

Published: 20 September 2019 Publication History

Abstract

Indonesia's Tourism industries is the second-best contributor to country's foreign exchange income for years. The growth it produced were in range of 7 to 10 percent per year since 2009. In reality, Bali is always at the top of the mind among majority of international tourists inspite of many hidden gems with spectacular qualities to rival Bali's popularity. Therefore, Indonesia's government has set new tourist destinations to increase their presence thus increasing visitation numbers. Researches on utilizing big data to support industry 4.0 model in tourism businesses are encouraged as part of national research priorities. Data Analytics models such as Sentiment Analysis and Topic Modelling can be used to reveal hidden patterns from abundant user-generated content data available in social media sites, one of which, TripAdvisor. This study aims to mine the visitors' perceptions of 10 most visited sites in Indonesia. Emotions and topics discussed in comments are two features to be extracted. Using data mining framework, five types of emotion and topics related to tourism were discovered. Data collection was done using Parsehub to acquire 3494 comments generated in 4 years. Both Sentiment Analysis and Topic Modelling were processed in Orange 3. Results shows that Joy is the most prominent emotion accompanying visitors' experiences. Topic modeling shows several important keywords toward preferences. Results of this study can be used to improve Indonesia's tourism stakeholder's decision quality especially in terms of marketing and operations.

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Cited By

Agustina CPurwanto PFarikhin F(2024)Enhancing Sentiment Analysis Accuracy in Borobudur Temple Visitor Reviews through Semi-Supervised Learning and SMOTE UpsamplingJournal of Advances in Information Technology10.12720/jait.15.4.492-49915:4(492-499)Online publication date: 2024
https://doi.org/10.12720/jait.15.4.492-499
SEZGİN MKARAGÖZ B(2023)Turistik Destinasyon Tanıtımında Sosyal Medyanın Rolü: Göbeklitepe ÖrneğiThe Role of Social Media in the Promotion of Touristic Destination: The Example of GöbeklitepeAlanya Akademik Bakış10.29023/alanyaakademik.12292297:3(1161-1176)Online publication date: 29-Sep-2023
https://doi.org/10.29023/alanyaakademik.1229229
Alamsyah NSaparudin Kurniati A(2023)A Novel Airfare Dataset To Predict Travel Agent Profits Based On Dynamic Pricing2023 11th International Conference on Information and Communication Technology (ICoICT)10.1109/ICoICT58202.2023.10262694(575-581)Online publication date: 23-Aug-2023
https://doi.org/10.1109/ICoICT58202.2023.10262694
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Index Terms

Mining Tourist's Perception toward Indonesia Tourism Destination Using Sentiment Analysis and Topic Modelling
1. Applied computing
  1. Law, social and behavioral sciences
    1. Sociology

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CCIOT '19: Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things

September 2019

134 pages

ISBN:9781450372411

DOI:10.1145/3361821

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Waseda University: Waseda University

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Published: 20 September 2019

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CCIOT 2019: 2019 4th International Conference on Cloud Computing and Internet of Things

September 20 - 22, 2019

Tokyo, Japan

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Cited By

Agustina CPurwanto PFarikhin F(2024)Enhancing Sentiment Analysis Accuracy in Borobudur Temple Visitor Reviews through Semi-Supervised Learning and SMOTE UpsamplingJournal of Advances in Information Technology10.12720/jait.15.4.492-49915:4(492-499)Online publication date: 2024
https://doi.org/10.12720/jait.15.4.492-499
SEZGİN MKARAGÖZ B(2023)Turistik Destinasyon Tanıtımında Sosyal Medyanın Rolü: Göbeklitepe ÖrneğiThe Role of Social Media in the Promotion of Touristic Destination: The Example of GöbeklitepeAlanya Akademik Bakış10.29023/alanyaakademik.12292297:3(1161-1176)Online publication date: 29-Sep-2023
https://doi.org/10.29023/alanyaakademik.1229229
Alamsyah NSaparudin Kurniati A(2023)A Novel Airfare Dataset To Predict Travel Agent Profits Based On Dynamic Pricing2023 11th International Conference on Information and Communication Technology (ICoICT)10.1109/ICoICT58202.2023.10262694(575-581)Online publication date: 23-Aug-2023
https://doi.org/10.1109/ICoICT58202.2023.10262694
Sumartini Saraswati NDarma Putra ISudarma MSukarsa I(2023)The Image of Tourist Attraction in Bali Based on Big Data Analytics and Sentiment Analysis2023 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS)10.1109/ICSGTEIS60500.2023.10424322(82-87)Online publication date: 2-Nov-2023
https://doi.org/10.1109/ICSGTEIS60500.2023.10424322
Kristanti NRamantoko G(2023)Sentiment-Score Analysis of P2P Lending Industry on Android Applications in Indonesia2023 1st International Conference on Advanced Engineering and Technologies (ICONNIC)10.1109/ICONNIC59854.2023.10467273(91-96)Online publication date: 14-Oct-2023
https://doi.org/10.1109/ICONNIC59854.2023.10467273
Dalipi FKastrati ZÖberg T(2023)The Impact of Artificial Intelligence on Tourism Sustainability: A Systematic Mapping Review2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)10.1109/ICCIKE58312.2023.10131818(119-125)Online publication date: 9-Mar-2023
https://doi.org/10.1109/ICCIKE58312.2023.10131818
Pallawala DHaddela P(2023)A Comparison of Topic Modeling Techniques for Sinhala2023 5th International Conference on Advancements in Computing (ICAC)10.1109/ICAC60630.2023.10417327(376-381)Online publication date: 7-Dec-2023
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Álvarez-Carmona MAranda RRodríguez-Gonzalez AFajardo-Delgado DSánchez MPérez-Espinosa HMartínez-Miranda JGuerrero-Rodríguez RBustio-Martínez LDíaz-Pacheco Á(2022)Natural language processing applied to tourism research: A systematic review and future research directionsJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2022.10.01034:10(10125-10144)Online publication date: Nov-2022
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ÖZEN A(2021)Evaluation of tourist reviews on TripAdvisor for the protection of the world heritage sites: Text mining approachJournal of Multidisciplinary Academic Tourism10.31822/jomat.8761756:1(37-46)Online publication date: 31-Jul-2021
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Irawan HAtha Ganiza R(2021)Analyzing Tourist's Movement in Sarbagita Metropolitan Area based on Geotagged Photo in FlickrProceedings of the 2021 6th International Conference on Cloud Computing and Internet of Things10.1145/3493287.3493296(60-67)Online publication date: 22-Sep-2021
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