Social Networks
Social networks are modeled as graphs where people are vertices and friendships are edges. This enables analysis of communities, influence, and connections.
Applications:
Friend recommendations (friends of friends)
Community detection (clusters)
Six degrees of separation
Influencer identification (high degree centrality)
Transportation Networks
Roads, flights, railways as graphs:
Vertices: Cities or intersections
Edges: Roads or flights
Weights: Distance, time, or cost
Algorithms:
Shortest path: Dijkstra's algorithm
Minimum spanning tree: Kruskal's or Prim's
Route optimization: Traveling salesman problem
Computer Networks
Internet and network infrastructure:
Vertices: Routers, switches, computers
Edges: Physical or logical connections
Key problems:
Routing: Finding best path for data packets
Reliability: Ensuring connectivity despite failures
Load balancing: Distributing traffic across paths
Other Applications
Dependency Graphs:
Software dependencies, task scheduling
Topological sort determines execution order
Map Coloring:
Adjacent regions must have different colors
Four Color Theorem: 4 colors suffice for planar maps
Recommendation Systems:
Bipartite graphs of users and products
Collaborative filtering based on graph patterns
Biological Networks:
Protein interactions, food webs, neural networks