Note: This article was written while conducting research for the Polis Foundation and was first published on their blog here.
This is a video of a randomly growing network using a variation of the preferrential attachment network generation model.
The network begins with 5 connected agents and adds 3 agents per time step for 208 steps (626 final agents).
Each newly introduced agent adds 2 new attachments randomly selected using the preferrential attachment approach, which weights an attachment towards agents that have more connections.
At each time step 2% of existing agents, selected randomly, also add 2 new random attachments using prefferential attachment.
Agent size (cirlce diameter) and color is proportional to the number of connections each agent possesses.
There is no strong motivation for the choice of these parameters - but it makes for a pretty video!