This project simulates techniques used in social media analysis to determine the set of influencers out of a graph containing millions of users and connections.The project aims at applying algorithms based on graph theory to compute the centrality property for each node in the graph.
- Degree Centrality
The degree of centrality of a node is the number of nodes connected to this node.
- Closeness Centrality
Closeness centrality indicates how close a node is to all other nodes in the network. It is calculated as the average of the shortest path length from the node to every other node in the network.To calculate closeness centrality we use Dijestra Algorithm
The Only requirment is to use visual studio to run the two algorithms as it's not gurranted to work on other compilers.
The Centralitey calculation and the graph virsualization are completely independent. So you need to run the c++ code first and then add the results manually in the javascript application