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Part 1: Document Description
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Citation |
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Title: |
The Mobility, Sentiment and Problems Identification Analysis in Tourism Industry using Social Media Data |
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Identification Number: |
doi:10.34820/FK2/ODPSTG |
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Distributor: |
Telkom University Dataverse |
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Date of Distribution: |
2022-09-21 |
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Version: |
1 |
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Bibliographic Citation: |
Tekom University, Dian Puteri Ramadhani, 2022, "The Mobility, Sentiment and Problems Identification Analysis in Tourism Industry using Social Media Data", https://doi.org/10.34820/FK2/ODPSTG, Telkom University Dataverse, V1 |
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Citation |
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Title: |
The Mobility, Sentiment and Problems Identification Analysis in Tourism Industry using Social Media Data |
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Identification Number: |
doi:10.34820/FK2/ODPSTG |
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Authoring Entity: |
Tekom University, Dian Puteri Ramadhani (Fakultas Ekonomi dan Bisnis: KK ICT Based Management (IBM)) |
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Distributor: |
Telkom University Dataverse |
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Access Authority: |
Tekom University, Dian Puteri Ramadhani |
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Depositor: |
Tekom University, Dian Puteri Ramadhani |
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Date of Deposit: |
2022-09-21 |
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Study Scope |
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Keywords: |
Business and Management |
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Abstract: |
Tourism industries have the potential to contribute to the country's income, and as they should, we expect this industry to continue to grow each year. Indonesia is one of the well-known countries with incredible destinations to visit by domestic and international tourists that are continuously growing. There are many ways to determine a suitable strategy to understand tourist behavior, such as understanding tourist mobility, sentiment, and problems. Using tourist reviews or user-generated content (UGC) data on the Tripadvisor website, we employ social network analysis (SNA) to identify tourist mobility, favorite and in-between destination using network metrics and measurements. We use sentiment analysis to classify tourist sentiment. And multiclass text classification method to find out various problems in tourist reviews. We also construct a text corpus for the tourism domain to classify tourism problems. The results represent the complex tourist mobility to recognize the favorite destination, the tourist sentiment in each destination, and the problem in Bali tourism. The combined model benefits many stakeholders such as tourists, the government, and business organizations. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Label: |
dataset-pariwisata-putu.csv |
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Notes: |
text/csv |