Evaluation of tourist sites through sentiment analysis of comments issued by users on social networks

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Published : 2022-06-30
DOI : https://doi.org/10.37815/rte.v34n2.921
Keywords :
Social Networks, Tourism, Sentiment Analysis, Big Data
Nelson Herrera Herrera
https://orcid.org/0000-0002-5781-6444
Nelson Salgado Reyes
https://orcid.org/0000-0001-8908-7613
Abstract

This research aims to present the usefulness of sentiment analysis in the comments issued by users of tourism services on social networks (Twitter and Trip Advisor), which allows rating the level of such services. This case study is set in the city of Quito-Ecuador.  The research develops a computer system using Big Data tools (Python, Node.Js, Mongo DB) to collect, store, and process large amounts of information. The Node.js programming language libraries, Puppeteer and Sentiment, make it possible to obtain comments from the social networks Twitter and Trip Advisor and determine a score for the observed tourist destination. Among the novel aspects of this research is the use of the social network Twitter as a source of data origin and web scraping techniques from the Trip Advisor site. This study uses the Twitter Application Programming Interface (API) to obtain data from this social network in real-time, facilitating the evaluation of the tourist services. Results determine that this tool allows the generation of knowledge to decide the quality level of the services received in the visited sites.

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How to Cite
Herrera Herrera, N. I., & Salgado Reyes, N. E. (2022). Evaluation of tourist sites through sentiment analysis of comments issued by users on social networks. Revista Tecnológica - ESPOL, 34(2), 125-139. https://doi.org/10.37815/rte.v34n2.921
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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