Dataset of Tourist Sentiments and Satisfaction in African Destinations: Insights from User-Generated Content on TripAdvisor

Published: 11 February 2025| Version 1 | DOI: 10.17632/6tyv663nrs.1
Contributors:
Isaac Ankrah, Esi Akyere Mensah, Doreen Nyarko Anyamesem Odame , Theresa Obuobisa-Darko, Robert Ebo Hinson

Description

This article describes a dataset of user-generated content (UGC) extracted from Tripadvisor, encompassing 5,043 tourist reviews from ten African destinations between August 2018 and August 2023. The data was systematically scraped using Tripadvisor’s scraping operator, ensuring accuracy and relevance. Preprocessing techniques were applied to clean and refine the data while preserving user sentiments and feedback. The data includes structured fields such as destination names, timestamps, and review text. This dataset is valuable for tourism researchers, policymakers, and industry stakeholders seeking insights into destination popularity, visitor experiences, and service quality. It supports trend analysis, predictive modeling, and comparative studies of regional tourism patterns. The structured format allows integration with other datasets for advanced tourism analytics. Through a longitudinal view of tourist sentiments, this dataset offers a valuable resource for understanding evolving travel behaviors and optimizing destination management strategies in Africa and beyond.

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Institutions

Ghana Technology University College

Categories

Tourist Satisfaction Study, Sentiment Analysis, User-Generated Content

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