Great article and the interactive graphs work well to explain concepts.<p>I can think of a few extensions: make it more realistic with a global map of fiber-optic cable networks and local extensions, and then compare how information spreads through things like peer-to-peer sharing vs. information posted to 'central authorities' like Twitter. (Notably there was also that study that showed false information spread faster across Twitter than accurate information, attributed to the 'surprise factor'). This could also be modified to include the authoritarian filter effect (i.e. how does China's 'Great Firewall' affect the spread of information, for example).<p>With respect to this simple nearest-neighbor model, I suppose a complicating factor would be long-distant transport from a given node to a distant node by some out-of-plane connection method (i.e. Covid spread rapidly by airplane, for example).<p>The article really shows that graph-based network thinking is a great way of approaching these problems, nice work.