Given an instance of set of nodes (users) in a social network graph, the aim is to find the influencing (important) users and to predict the likelihood of a future association (edge) between two nodes, knowing that there is no association between the nodes in the current state of the graph.
Here I have done the social link analysis on Facebook.
The edges described in the problem statement could be of any form: friendship, collaboration, following or mutual interests. Here, we specifically study and build our model over Facebook's social network, with the following areas of motivation:
- General application of friends recommendation to a particular user.
- Predicting hidden links in a social network group formed by terrorists along with identification of their leaders/ key influencers.
- Targeted marketing of products: Marketing through highly influential individuals and also identifying plausible customers.
- Suggesting promising interactions or collaborations that have not yet been identified within an organization.
- In Bioinformatics, link prediction can be used to find interactions between proteins. The following model can be extended or modified to cater to the needs of various other social networks like Twitter, Google+, Foursquare, etc.