Modeling the development of a social network: the game "Social Life"

The article is inspired by a previous post about the game "Life" Conway: Let's play in life

Let's set ourselves the goal of simulating the work of a social network using an analogue of the game “Life” - let's call such a game.

"Social life". For simplicity, we will assume that all personal computers in the world can be placed in the cells of the game field of life, while we will have computers of people who often communicate with each other nearby. In other words, we will assume that each person has 8 acquaintances with whom he constantly communicates (this is a rather strong assumption, but for simplicity we will have to do it). We assume that a cell is alive if a person has become part of a social network. We will also assume that a person will become a member of a social network when he learns about this network from his friends. Also, for simplicity, we will assume that the probability that a member of the social network will send out invitations is 1/2; the probability that a non-member accepts an invitation is 2/3. Thus, in order for a user to become a member of a social network, he must have 3 familiar members of this network.

Modifying, in accordance with the foregoing, the original rules of the game "Life", we obtain the following rules of the game for modeling the behavior of social networks.

• Each cell can be in one of two states: live (filled) or dead (empty);
• Each turn of each cell determines its state and the state of all its 8 neighbors;
• If it is an empty cell and neighbors 3 or more , then this cell comes to life. In all other cases, the empty cell remains empty;
• If it is a living cell, then the number of living neighbors is calculated;
• If neighbors are 0 or 1, then the cell dies of loneliness;
• If there are 2 or 3 neighbors, then the cell continues to live;
• If there are 4 neighbors or more, then the cell also continues to live ;
• With probability P1, at every turn, a dead cell can spontaneously come to life (corresponds to the influx of users who learned about the existence of a social network from its advertising, is proportional to the quantity and quality of advertising);
• With probability P2, on each move a living cell can spontaneously die (corresponds to the natural outflow of users who are tired of the social network, is inversely proportional to the quantity and quality of services in the social network);

Bold italics marked differences from the rules of the game "Life".

The resulting Social Life game will be a self-organizing system that can be exposed to external influences by changing the probability values ​​P1 (impact through advertising) and P2 (impact through launching new services). If you program the game “Social Life”, you can model the behavior of real-life social networks, in particular, predict the reaction in advance and calculate the effectiveness of advertising social networks and launching new services in them. Accordingly, such a model could be useful in developing a strategy for launching and developing social networks, since would allow to develop an optimal strategy for promoting a social network.

This topic is written by the user gorod , who due to lack of karma could not publish it. I have a very big request to all - give him some karma so that he can write articles further.