Prediction of Preferred Personality for Friend Recommendation in Social Networks using Artificial Neural Network

Social Networking sites have nowadays become the most common way to communicate over online for people around the world. For making friends in social network, there remains an underlying friend recommendation framework which suggests friends to the users. However, most of the existing friend recommendation frameworks consider only the number of mutual friends, geo-location, mutual interests etc. to recommend one person as a friend to another. But, in real life, people, who have similar personalities, tend to become friends to each other, application of which is completely missing in the modern friend recommendation frameworks. Hence, we have proposed a personality based friend recommendation framework in this paper, which consists of a 3-Layered Artificial Neural Network for friend preference classification and a distance-based sorted subset selection procedure for friend recommendation. Our model tends to achieve a fairly high precision, recall, fl-measure and accuracy of around 85 %,85%,82% and 83% respectively in the friend choice classification task.