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Topological stability and textual differentiation in human interaction networks: statistical analysis, visualization and linked data

Fabbri, Renato

Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Instituto de Física de São Carlos 2017-05-08

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  • Título:
    Topological stability and textual differentiation in human interaction networks: statistical analysis, visualization and linked data
  • Autor: Fabbri, Renato
  • Orientador: Oliveira Junior, Osvaldo Novais de
  • Assuntos: Análise De Redes Sociais; Dados Ligados; Redes Complexas; Mineração De Texto; Reconhecimento De Padrões; Social Network Analysis; Pattern Recognition; Linked Data; Complex Networks; Text Mining
  • Notas: Tese (Doutorado)
  • Descrição: This work reports on stable (or invariant) topological properties and textual differentiation in human interaction networks, with benchmarks derived from public email lists. Activity along time and topology were observed in snapshots in a timeline, and at different scales. Our analysis shows that activity is practically the same for all networks across timescales ranging from seconds to months. The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered. The activity of participants follows the expected scale-free outline, thus yielding the hub, intermediary and peripheral classes of vertices by comparison against the Erdös-Rényi model. The relative sizes of these three sectors are essentially the same for all email lists and the same along time. Typically, 3-12% of the vertices are hubs, 15-45% are intermediary and 44-81% are peripheral vertices. Texts from each of such sectors are shown to be very different through direct measurements and through an adaptation of the Kolmogorov-Smirnov test. These properties are consistent with the literature and may be general for human interaction networks, which has important implications for establishing a typology of participants based on quantitative criteria. For guiding and supporting this research, we also developed a visualization method of dynamic networks through animations. To facilitate verification and further steps in the analyses, we supply a linked data representation of data related to our results.
  • DOI: 10.11606/T.76.2017.tde-11092017-154706
  • Editor: Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Instituto de Física de São Carlos
  • Data de criação/publicação: 2017-05-08
  • Formato: Adobe PDF
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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