Sentiment Analysis of Social Media Data in Tourism Destination Studies: A Systematic Literature Review

Abstract

Sentiment analysis of social media data has emerged as a valuable tool for understanding tourist perceptions and behaviors. To the best of the author’s knowledge, this is the first systematic review that precisely focuses on tourism destination studies applying sentiment analysis to social media data. It highlights methodological patterns, identifies underutilized platforms and techniques, and proposes future research directions for this growing interdisciplinary field. A systematic review of research papers published between 2016 and 2024 was conducted using reliable and credible databases, including ScienceDirect, IEEE Xplore, Emerald Insight, Springer, Scopus, Google Scholar and Web of Science. After the initial and thorough screening of published papers, 29 out of 81 articles were selected for the review process. The articles were reviewed based on the objectives and methodology of the study. The results show that most studies used machine learning and lexicons techniques for sentiment analysis of social media data, primarily from Twitter and TripAdvisor. There is strong empirical evidence that social media plays a significant role in shaping the image of tourist destinations.