Dataset Review Bali’s Cultural Attractions (Multilingual)

Published: 8 December 2025| Version 1 | DOI: 10.17632/5zzdy3f48k.1
Contributor:
Nengah Widya Utami

Description

The dataset contains 7,878 tourist reviews of Balinese cultural performances, including the Kecak and Fire Dance, collected from Tripadvisor and Google Maps. The reviews span the years 2011 to 2025, with the following columns: source – The platform from which the review was collected (Tripadvisor and Google Maps). lang – The language of the review (English, Indonesian, French, Japanese, German, etc.). object – The attraction or activity being reviewed (entries include "Kecak Dance, Fire Dance, Barong Dance, Legong Dance, Keris Dance, Sangyang Dance"). location – The location of the attraction (entries include Pecatu, Ubud, Sukawati, Batubulan, Kesiman). review – The textual content of the tourist review, ranging from positive experiences (e.g., appreciation of the cultural performance, sunset views, and traditional costumes) to negative experiences (e.g., overcrowding, uncomfortable seating, and safety concerns due to monkeys). Reviews provide detailed descriptions of visitor experiences, including performance, venue, organization, and environmental factors. year – The year of the review (2011–2025). Overall, this dataset captures tourist sentiment, experiences, and cultural insights regarding Balinese cultural attractions, making it suitable for sentiment analysis, text mining, or cultural tourism research. The reviews highlight both positive aspects, such as unique cultural performances and scenic backdrops, and negative aspects, such as crowd management, safety issues, and visitor discomfort.

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Steps to reproduce

The dataset was compiled by crawling tourist reviews from Tripadvisor and Google Maps for various Balinese cultural performances, including Kecak Dance, Fire Dance, Barong Dance, Legong Dance, Keris Dance, and Sangyang Dance. Reviews were collected across multiple locations in Bali, such as Pecatu, Ubud, Sukawati, Batubulan, and Kesiman, spanning the years 2011 to 2025. During the collection process, care was taken to extract relevant information, including the review text, language, source platform, attraction, location, and year. The resulting dataset provides a comprehensive representation of visitor experiences and perceptions across different performances and locations.

Categories

Tourism, Data Science, Big Data, Informatics, Cultural Tourism, Database, Sentiment Analysis

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