There are different methods of detecting influencer people in a social network. In this project two of these methods will be used. In the given directional graph, the nodes provide the first and last name information of the people, directional links, on the other hand, show the connections to the people the person is following. On this graph the steps of the operations to be performed are as follows:
1- When finding out which nodes belong to influencer people in a graph, the calculation for each node is you need to do. But also to make transactions for people with few followers, especially on a large network it will be an unnecessary waste of time. To eliminate nodes that do not have the potential to become influencers, write the function that performs the following operation: By calculating the in-degree value of the nodes (the connections towards it), the in-degree eliminate the nodes whose value is less than a given M value. After the elimination process, also eliminate the nodes whose in degree value falls below M. This operation is performed by the in-degree value of M repeat until there is no knot left under it.
2- For nodes that are not eliminated in the first step, the total coming directly and indirectly to a node is write the function that calculates the number of connections.
3- In the nodes that you calculated in the first figure above, X>M, the in-degree value is X the total number of incoming connections that is greater than-equal to the number and that you calculated in the second figure is a Y nodes that are greater than-equal in value belong to influencer people.
