Analyzing A Touristic Event Popularity Using Social Networks

  • Pedro Pongelupe Lopes PUC-Minas
  • Humberto T. Marques-Neto PUC-Minas

Resumo


Context-aware recommendation systems use contextual data to recommend a fully personalized suggestion to their users, for instance, using the massive workloads produced by the usage of mobile apps. In this paper, we collected and analyzed a dataset from social media related to the Belo Horizonte's 2020 Carnival to understand how this event attracts tourists (or Belo Horizonte's non-resident), analyzing their interactions with a large recommendation system. We built a point-of-view of an event mixing its features in two social networks: Twitter and Google Review. Our results show that combining traits lead to better information about the given context using social networks. It helps both the tourists choosing where to travel and the local establishments to provide better services.
Palavras-chave: Social Media, Tourists, Complex Networks, Mobility, Cultural Behavior
Publicado
30/11/2020
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LOPES, Pedro Pongelupe; MARQUES-NETO, Humberto T.. Analyzing A Touristic Event Popularity Using Social Networks. In: SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 1. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 333-336.