Introduction to the Analysis of Tourism Services through Feelings Mining
Hector F. Gomez 1 * , Edwin Fabricio Lozada 2, Carlos Eduardo Martínez 2, Freddy Patricio Baño 2, Gustavo Adolfo Álvarez 2, Walter V. Culque 2, Natalia Soledad Bustamante-Sánchez 3, Rosario Estefanía Sánchez Cevallos 3
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1 Facultad de Ciencias Humanas y de la Educacion, UHuachi- Ambato, ECUADOR
2 Carrera de Sistemas, Universidad Regional Autónoma de los Andes–Uniandes-Km. 5½ vía a Baños, ECUADOR
3 Universidad Técnica Particular de Loja, Departamento de ciencias Administrativas, Sección de Hotelería y Turismo, ECUADOR
* Corresponding Author


One of the sources of information to detect the level of customer satisfaction is the set of reviews they leave on websites such as Trip Advisor. A problem arises when there is a large number of reviews and administrators have difficulty identifying those that reflect the client's feelings from the reviews. For this study, some applications generated in the Python programming language were used in order to assign an excellent and bad criterion by adding a feeling textually. The Sentistrength classifier was also used, which analyzes text to return a value of positive or negative sentiment; these two contexts were used mathematically and statistically to obtain referential data based on an analysis of the ROC curve with values of true positives and true negatives as well as false positives and false negatives.


This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

J INFORM SYSTEMS ENG, 2018 - Volume 3 Issue 4, Article No: 33

Publication date: 10 Nov 2018

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Article Downloads: 789

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