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@article{ Manosso2021,
 title = {Using sentiment analysis in tourism research: A systematic, bibliometric, and integrative review},
 author = {Manosso, Franciele Cristina and Domareski Ruiz, Thays Cristina},
 journal = {Journal of Tourism, Heritage & Services Marketing},
 number = {2},
 pages = {16-27},
 volume = {7},
 year = {2021},
 issn = {2529-1947},
 doi = {},
 urn = {},
 abstract = {Purpose: Sentiment analysis is built from the information provided through text (reviews) to help understand the social sentiment toward their brand, product, or service. The main purpose of this paper is to draw an overview of the topics and the use of the sentiment analysis approach in tourism research.
Methods: The study is a bibliometric analysis (VOSviewer), with a systematic and integrative review. The search occurred in March 2021 (Scopus) applying the search terms "sentiment analysis" and "tourism" in the title, abstract, or keywords, resulting in a final sample of 111 papers. 
Results: This analysis pointed out that China (35) and the United States (24) are the leading countries studying sentiment analysis with tourism. The first paper using sentiment analysis was published in 2012; there is a growing interest in this topic, presenting qualitative and quantitative approaches. The main results present four clusters to understand this subject. Cluster 1 discusses sentiment analysis and its application in tourism research, searching how online reviews can impact decision-making. Cluster 2 examines the resources used to make sentiment analysis, such as social media. Cluster 3 argues about methodological approaches in sentiment analysis and tourism, such as deep learning and sentiment classification, to understand the user-generated content. Cluster 4 highlights questions relating to the internet and tourism.
Implications: The use of sentiment analysis in tourism research shows that government and entrepreneurship can draw and enhance communication strategies, reduce cost, and time, and mainly contribute to the decision-making process and understand consumer behavior.},
 keywords = {Tourismus; tourism; Online-Medien; online media; Internet; Internet; Entscheidungsfindung; decision making; Konsumverhalten; consumption behavior; Bewertung; evaluation; Gastgewerbe; hotel and restaurant trade; Textanalyse; text analysis; Computerlinguistik; computational linguistics; Soziale Medien; social media}}