Instantly share code, notes, and snippets.

What would you like to do?
Visualize Twitter Network using the NetworkX python Library
import networkx as net
import matplotlib.pyplot as plt
from collections import defaultdict
import math
twitter_network = [ line.strip().split('\t') for line in file('twitter_network.csv') ]
o = net.DiGraph()
hfollowers = defaultdict(lambda: 0)
for (twitter_user, followed_by, followers) in twitter_network:
o.add_edge(twitter_user, followed_by, followers=int(followers))
hfollowers[twitter_user] = int(followers)
SEED = 'TEDxSingapore'
# centre around the SEED node and set radius of graph
g = net.DiGraph(net.ego_graph(o, SEED, radius=4))
def trim_degrees_ted(g, degree=1, ted_degree=1):
g2 = g.copy()
d =
for n in g2.nodes():
if n == SEED: continue # don't prune the SEED node
if d[n] <= degree and not n.lower().startswith('ted'):
elif n.lower().startswith('ted') and d[n] <= ted_degree:
return g2
def trim_edges_ted(g, weight=1, ted_weight=10):
g2 = net.DiGraph()
for f, to, edata in g.edges_iter(data=True):
if f == SEED or to == SEED: # keep edges that link to the SEED node
g2.add_edge(f, to, edata)
elif f.lower().startswith('ted') or to.lower().startswith('ted'):
if edata['followers'] >= ted_weight:
g2.add_edge(f, to, edata)
elif edata['followers'] >= weight:
g2.add_edge(f, to, edata)
return g2
print 'g: ', len(g)
core = trim_degrees_ted(g, degree=235, ted_degree=1)
print 'core after node pruning: ', len(core)
core = trim_edges_ted(core, weight=250000, ted_weight=35000)
print 'core after edge pruning: ', len(core)
nodeset_types = { 'TED': lambda s: s.lower().startswith('ted'), 'Not TED': lambda s: not s.lower().startswith('ted') }
nodesets = defaultdict(list)
for nodeset_typename, nodeset_test in nodeset_types.iteritems():
nodesets[nodeset_typename] = [ n for n in core.nodes_iter() if nodeset_test(n) ]
pos = net.spring_layout(core) # compute layout
colours = ['red','green']
colourmap = {}
# draw nodes
i = 0
alphas = {'TED': 0.6, 'Not TED': 0.4}
for k in nodesets.keys():
ns = [ math.log10(hfollowers[n]+1) * 80 for n in nodesets[k] ]
print k, len(ns)
net.draw_networkx_nodes(core, pos, nodelist=nodesets[k], node_size=ns, node_color=colours[i], alpha=alphas[k])
colourmap[k] = colours[i]
i += 1
print 'colourmap: ', colourmap
# draw edges
net.draw_networkx_edges(core, pos, width=0.5, alpha=0.5)
# draw labels
alphas = { 'TED': 1.0, 'Not TED': 0.5}
for k in nodesets.keys():
for n in nodesets[k]:
x, y = pos[n]
plt.text(x, y+0.02, s=n, alpha=alphas[k], horizontalalignment='center', fontsize=9)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment