Social network analysis with Python
What do we need?
- Motivation.
- Data.
- Tools.
- Example.
Motivation
Understanding a bit about social networks APIs and create visualization over real data.
Data
Tools
- Python (pandas,networkx,matplotlib...).
- Twitter API.
Example
- Details.
- Results.
Un-Pruned graph
Prunning
remove = []
for node in G.nodes():
if G.degree(node) < 2:
remove.append(node)
G.remove_nodes_from(remove)
Pruned graph
Graph info
Number of nodes: 1277
Number of edges: 11512
Average degree: 18.0298
Some coloring...
Centrality
This indicators identify the most important vertices within a graph.
highest degree
map=[]
for node in G.nodes():
map.append(G.degree(node))
map.append(G.degree(node))
draw_network with: node_color=map , node_size=map
Highest degrees
Degree centrality
color_map=[]
size_map= []
test = nx.degree_centrality(G)
for node in G.nodes():
size_map.append(G.degree(node))
color_map.append(test[node])
draw_network with: node_color=map , node_size=size_map
Degree centrality
