Utilizando Métricas de Ego-network para Validação de Atributos dos Perfis de Usuários de Redes Sociais On-line

  • Hélder Seixas Lima PUC Minas
  • Humberto Torres Marques-Neto PUC Minas

Resumo


Os usuários de uma rede social on-line são identificados por meio dos seus perfis, os quais geralmente são compostos por atributos como nome, sexo, idade, cidade, entre outros. Como os atributos de perfil são autodeclarados, surge a possibilidade de que usuários mal-intencionados criem contas com informações falsas. Este trabalho propõe um framework que determina um nível de confiabilidade para cada atributo utilizado no perfil de um usuário de rede social on-line. O framework proposto utiliza métricas no contexto de ego-network para verificar fenõmenos comuns nas redes sociais. A proposta foi avaliada experimentalmente com duas amostras reais e duas amostras artificiais de duas redes sociais: o Facebook e o Google+. As amostras artificiais simulam usuários falsos. Os resultados mostraram que os níveis de confiabilidade determinados pelo framework são mais elevados para a maioria dos atributos de perfil dos usuários das amostras reais quando comparados aos das amostras artificiais.

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Publicado
10/05/2018
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LIMA, Hélder Seixas; MARQUES-NETO, Humberto Torres. Utilizando Métricas de Ego-network para Validação de Atributos dos Perfis de Usuários de Redes Sociais On-line. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 36. , 2018, Campos do Jordão. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 365-378. ISSN 2177-9384. DOI: https://doi.org/10.5753/sbrc.2018.2428.