Prediction of tourist traffic to Peru by using sentiment analysis in Twitter social network

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Resumen

This work involves the use of tweets, from Twitter social network in which the users manifest the desire to travel to the country of Peru, to build a predictive tool of tourist traffic. To make this task has been made automated collection of tweets using web crawling and has been used Naive Bayes algorithm for sorting tweets as part of sentiment analysis. In the final part, we shown the results of the application of the tool for predicting the influx of tourists to Peru.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2015 41st Latin American Computing Conference, CLEI 2015
EditoresAlex Cuadros-Vargas, Hector Cancela, Ernesto Cuadros-Vargas
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781467391436
DOI
EstadoPublicada - 16 dic. 2015
Evento41st Latin American Computing Conference, CLEI 2015 - Arequipa, Perú
Duración: 19 oct. 201523 oct. 2015

Serie de la publicación

NombreProceedings - 2015 41st Latin American Computing Conference, CLEI 2015

Conferencia

Conferencia41st Latin American Computing Conference, CLEI 2015
País/TerritorioPerú
CiudadArequipa
Período19/10/1523/10/15

Nota bibliográfica

Publisher Copyright:
© 2015 IEEE.

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