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

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

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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.


tourism, semantic, orientation, opinion




Gomez, H. F., Lozada, E. F., Martínez, C. E., Baño, F. P., Álvarez, G. A., Culque, W. V., . . . Cevallos, R. E. S. (2018). Introduction to the Analysis of Tourism Services through Feelings Mining. Journal of Information Systems Engineering & Management, 3(4), 33.

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