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Internet ~ social network ~ 工教一 49771024 黃耀陞

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Social network analysis plays an important role in analyzing social relations and patterns of interaction among actors in a social network. Such networks can be casual, like those on social media sites, or formal, like academic social networks. Each of these networks is characterised by underlying data which defines various features of the network. Keeping in view the size and diversity of these networks it may not be possible to dissect entire network with conventional means. Social network visualization can be used to graphically represent these networks in a concise and easy to understand manner. Social network visualization tools rely heavily on quantitative features to numerically define various attributes of the network. These features also referred to as social network metrics used everyday mathematics as their foundations. In this paper we provide an overview of various social network analysis metrics that are commonly used to analyse social networks. Explanation of these metrics and their relevance for academic social networks is also outlined

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The social network analysis (SNA), branch of complex systems can be used in the construction of multiagent systems. This paper proposes a study of how social network analysis can assist in modeling multiagent systems, while addressing similarities and differences between the two theories. We built a prototype of multi-agent systems for resolution of tasks through the formation of teams of agents that are formed on the basis of the social network established between agents. Agents make use of performance indicators to assess when should change their social network to maximize the participation in teams.

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