Future Collaboration Prediction in Co-authorship Network

The advent of proliferation of social networking is high on use in present era. A co-authorship network which shows research collaborations, are an important class of social networks. Research collaborations often yield good results but organizing a research group is a tedious task. Every researcher is concerned to collaborate with the best expertise complimenting him. Although there was abundant research conducted to find future collaborators or links, very few of them are able to find out effective relationship among them. In this article, we propose a method that makes link predictions in co-authorship networks using supervised approach. The model extracts the features from the networks node and topological structure which can be good indicators of future collaborations. The proposed method was evaluated on synthetic as well as real social networks such as Net Science. Our experiment corroborated the results, and demonstrated the efficiency of the method.