Extração de Conhecimento e Análise Visual de Redes Sociais

Carla M. D. S. FreitasLuciana P. NedelRenata GalanteLuís C. LambAndré S. SpritzerSérgio FujiiJosé Palazzo M. de OliveiraRicardo M. AraújoMirella M. Moro

A social network is a graph where people or organizations (depending on the application) are represented as nodes connected by edges that can refer to either tight social bonds or some common, shared aspect. The graph structure analysis and the statistical analysis of specific node/edge attributes can reveal important individuals, relationships, and clusters. New information continues to be collected and stored, and size and complexity of the semantic graphs overwhelm the human cognitive abilities. Hence, it is necessary to improve the computational mechanisms to analyze such volume of data. In this paper, we focus on analyzing the information from social networks, extracting relevant knowledge, and visualizing the facts resultant from the analysis.

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