In the previous section, we investigated several types of graphs. We examined web pages connected by directed links and also a network of roads spanning multiple counties. In our analysis, we’ve mostly treated the network as frozen, static objects—we’ve counted neighboring nodes as though they were frozen clouds in a photograph. In real life, clouds are constantly in motion, and so are many networks. Most networks worth studying are perpetually buzzing with dynamic activity. Cars race across networks of roads, causing traffic congestion near popular towns. In that same vein, web traffic flows across the internet as billions of users explore the many web links. Our social networks are also flowing with activity as gossip, rumors, and cultural memes spread across tight circles of close friends. Understanding this dynamic flow can help uncover friend groups in an automated manner. Understanding the flow can also help us identify the most heavily trafficked web pages on the internet. Such modeling of dynamic network activity is critical to the function of many large tech organizations. In fact, one of the modeling methods presented in this section led to the founding of a trillion-dollar company.