Same Scenario as Barabasi

We mined the Facebook Page network using a breadth of first search method. We analyzed two networks. The first network we analyzed was the basic degree distribution of the Facebook Page Network. We looked at 4.8 million Brands, Public Figures and Organizations and obtained the degrees of each node. We aggregated these nodes to obtain a degree distribution. We found that this degree distribution followed a power law. This means that the normal distribution and normal statistics are invalid for comparing the relations between multiple profiles.

The second network we considered was analyzed topologically. We took each BPO and found the outdegree of each network. We then re-created the network to analyze the degree distribution and we also found this to be a power law. Furtehr, we found this network to have scale-free properties.

Breadth of First Search: The breadth of first search algorithm takes a node. Then we look to the neighbours of this node. Then we take the neighbours of these nodes. This is how large networks of connections, such as people are analyzed. Many nodes are reached in a small number of steps. In fact the average path length of a scale-free network is typically LOG(N).