Network Diagram

# === IMPORTS ===
import numpy as np
import matplotlib.pyplot as plt
import networkx as nx

# === USER-EDITABLE PARAMETERS ===
title = "Social Media Influence Network"
figsize = (14, 10)

# === EXAMPLE DATASET ===
np.random.seed(42)

# Node data: (name, type, followers)
nodes_data = [
    # Mega Influencers
    ('MegaStar A', 'Mega Influencer', 5000000),
    ('MegaStar B', 'Mega Influencer', 3500000),
    # Macro Influencers
    ('Lifestyle Pro', 'Macro Influencer', 800000),
    ('Tech Guru', 'Macro Influencer', 650000),
    ('Fitness Coach', 'Macro Influencer', 550000),
    # Micro Influencers
    ('Food Blogger', 'Micro Influencer', 120000),
    ('Travel Vlogger', 'Micro Influencer', 95000),
    ('Beauty Tips', 'Micro Influencer', 88000),
    # Brands
    ('Nike', 'Brand', 400000),
    ('Apple', 'Brand', 600000),
    ('Sephora', 'Brand', 250000),
    # Nano Influencers
    ('Local Chef', 'Nano Influencer', 8000),
    ('Yoga Life', 'Nano Influencer', 12000),
    ('Gamer Dude', 'Nano Influencer', 15000),
]

# Edge data: (source, target, weight)
edges_data = [
    ('MegaStar A', 'Lifestyle Pro', 85),
    ('MegaStar A', 'Nike', 95),
    ('MegaStar A', 'Tech Guru', 70),
    ('MegaStar B', 'Fitness Coach', 80),
    ('MegaStar B', 'Apple', 90),
    ('MegaStar B', 'Sephora', 75),
    ('Lifestyle Pro', 'Food Blogger', 65),
    ('Lifestyle Pro', 'Travel Vlogger', 60),
    ('Tech Guru', 'Gamer Dude', 55),
    ('Fitness Coach', 'Yoga Life', 70),
    ('Nike', 'Fitness Coach', 85),
    ('Apple', 'Tech Guru', 80),
    ('Sephora', 'Beauty Tips', 75),
    ('Food Blogger', 'Local Chef', 50),
    ('Beauty Tips', 'Local Chef', 45),
    ('MegaStar A', 'MegaStar B', 60),
]

# Create graph
G = nx.Graph()
for name, node_type, followers in nodes_data:
    G.add_node(name, type=node_type, followers=followers)
for source, target, weight in edges_data:
    G.add_edge(source, target, weight=weight)

# Print summary
print("=== Social Media Network Analysis ===")
print(f"\nNodes: {G.number_of_nodes()}")
print(f"Edges: {G.number_of_edges()}")
print(f"\nTop 5 by Degree:")
degrees = dict(G.degree())
for node, deg in sorted(degrees.items(), key=lambda x: x[1], reverse=True)[:5]:
    print(f"  {node}: {deg} connections")

# === CREATE NETWORK DIAGRAM ===
fig, ax = plt.subplots(figsize=figsize, facecolor='white')
ax.set_facecolor('white')

# Use Kamada-Kawai layout for better spacing
pos = nx.kamada_kawai_layout(G)

# Color mapping by type
color_map = {
    'Mega Influencer': '#E53935',
    'Macro Influencer': '#1E88E5', 
    'Micro Influencer': '#43A047',
    'Brand': '#FB8C00',
    'Nano Influencer': '#8E24AA'
}

# Node colors and sizes
node_colors = [color_map[G.nodes[node]['type']] for node in G.nodes()]
node_sizes = [np.log10(G.nodes[node]['followers']) * 120 for node in G.nodes()]

# Draw edges - thin gray lines
edge_widths = [G.edges[edge]['weight'] / 40 for edge in G.edges()]
nx.draw_networkx_edges(G, pos, width=edge_widths, alpha=0.5, 
                       edge_color='#999999', ax=ax)

# Draw nodes - solid circles with white border
nx.draw_networkx_nodes(G, pos, node_color=node_colors, node_size=node_sizes, 
                       edgecolors='white', linewidths=2, ax=ax)

# Draw labels - positioned below nodes
label_pos = {node: (coords[0], coords[1] - 0.08) for node, coords in pos.items()}
nx.draw_networkx_labels(G, label_pos, font_size=9, font_weight='bold', 
                        font_color='#333333', ax=ax)

# Legend
from matplotlib.patches import Patch
legend_elements = [
    Patch(facecolor=color, label=label, edgecolor='white', linewidth=1.5)
    for label, color in color_map.items()
]
legend = ax.legend(handles=legend_elements, loc='upper left', 
                   frameon=True, facecolor='white', edgecolor='#CCCCCC',
                   fontsize=10, title='Node Type', title_fontsize=11)

# Title
ax.set_title(title, fontsize=20, fontweight='bold', color='#333333', pad=15)

# Clean layout
ax.axis('off')
ax.margins(0.15)

plt.tight_layout()
plt.savefig('chart.png', dpi=150, bbox_inches='tight', facecolor='white')
print("Saved: chart.png")
plt.show()
# END-OF-CODE

=== Social Media Network Analysis ===

Nodes: 14
Edges: 16

Top 5 by Degree:
  MegaStar A: 4 connections
  MegaStar B: 4 connections
  Lifestyle Pro: 3 connections
  Tech Guru: 3 connections
  Fitness Coach: 3 connections
Saved: chart.png