L9; Clustering 1 Network Graphing Visualisation

Question 1

network science

Answer 1

network science is a new and emerging scientific discipline that examines the interconnections among diverse physical, informational, biological, cognitive and social networks.
it seeks to discover common principles, algorithms and tools that govern network behaviour.
network visualization allows you to identify, extract and classify new patterns in data and network structures.

Question 2

networks

Answer 2

a network is a collection of points joined together by lines.
the points are referred to as vertices or nodes and lines are referred to as edges.

Question 3

modularity

Answer 3

modularity measures how well a network decomposes into a community structure.
used to cluster a network graph into sub-networks.
modularity is the number of edges falling within groups minus the expected number in an equivalent network with edges placed at random.
modularity can be either positive or negative, with positive values indicating the possible presence of community structure.
high modularity score indicates sophisticated internal structure.

Question 4

centrality

Answer 4

degree centrality is nodes having many edges are central.

1. betweenness centrality nodes that lay on the shortest paths are central
2. closeness centrality nodes that are close to all other nodes are central.
3. eigenvector centrality nodes that are connectede to highly ranked nodes are central