Analyzing A Touristic Event Popularity Using Social Networks
Pages 269 - 272
Abstract
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.
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- Analyzing A Touristic Event Popularity Using Social Networks
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- CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
- CGIBR: Comite Gestor da Internet no Brazil
- CAPES: Brazilian Higher Education Funding Council
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Published: 30 November 2020
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- Short-paper
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- Refereed limited
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WebMedia '20: Brazillian Symposium on Multimedia and the Web
November 30 - December 4, 2020
São Luís, Brazil
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WebMedia '20 Paper Acceptance Rate 34 of 87 submissions, 39%;
Overall Acceptance Rate 270 of 873 submissions, 31%
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