Network analysis
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Network analysis is the analysis of networks through network theory (or more generally graph theory).
The networks may be real as in a social network, or virtual, such as the Internet.
Analysis include descriptions of structure, such as small-world networks, social circles or scale-free networks, optimisation, such as Critical Path Analysis and PERT (Program Evaluation & Review Technique), and properties such as flow assignment.
Social network analysis maps relationships between individuals in social networks.
[edit] Centrality measures
Information about the relative importance of nodes and edges in a graph can be obtained through centrality measures, widely used in disciplines like sociology. For example, eigenvector centrality uses the eigenvectors of the adjacency matrix to determine nodes that tend to be frequently visited.
[edit] Web link analysis
Several Web search ranking algorithms use eigenvector-based centrality metrics, including Google's PageRank, Kleinberg's HITS algorithm, and the TrustRank algorithm.
[edit] See also
- pt:Análise de redes
| This page uses content from the English-language version of Wikipedia. The original article was at Network analysis. The list of authors can be seen in the page history. As with Psychology Wiki, the text of Wikipedia is available under the GNU Free Documentation License. |
