Theory 1 : CGPA - Continuous Growth and Preferential Attachment

YAY! Theory time!! Okay, maybe not the best thing in the world, but important none the less.

As shown by Barabasi and team, real scenarios tend to follow a pattern for connection between nodes. But for all it's glory and charm, Math can never assure certainty, the best it can do is give you a probability for a connection to be formed. 

and then, with some magic, some connections are established

Something similar to this aforementioned "magic" is portrayed in the new series, Betas , nice timing, eh?!!
While one may argue that human connection is ultimately attributed to this 'magic' factor (others might use words like Charm, affection, courage, luck etc. ) , what math does is give us a tool to better understand what is happening, and peek into the how- and why- of it. 

The beauty of the model lies in the fact that it lets new nodes be a part of the network. "I don't need new friends, I have enough." - said no one ever.  This is what 'Continuous Growth' refers to.

Also, the part of the model about 'Preferential Attachment' says that heavily connected nodes are more likely to form new connections with an incoming node. In terms of a common man, it's like saying everyone at school knows the captain of the football team.

Keeping these two facts in mind, we'll focus on how hubs are formed around heavily connected nodes.

So now, I need to modify my existing model to act as a seed network and create a bigger network accounting for these two properties. Time to unleash the code monkey inside. So Long.

media courtesy : wikimedia.