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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2015 41st Latin American Computing Conference, CLEI 2015
EditorsAlex Cuadros-Vargas, Hector Cancela, Ernesto Cuadros-Vargas
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467391436
DOIs
StatePublished - 16 Dec 2015
Event41st Latin American Computing Conference, CLEI 2015 - Arequipa, Peru
Duration: 19 Oct 201523 Oct 2015

Publication series

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

Conference

Conference41st Latin American Computing Conference, CLEI 2015
Country/TerritoryPeru
CityArequipa
Period19/10/1523/10/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

  • Data Mining
  • Naive Bayes
  • Prediction
  • Sentiment Analysis
  • Social Network
  • Tourist Traffic
  • Twitter

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