Affiliation Influence on Recommendation in Academic Social Networks

Social networks have been the focus of many studies, from communities’ identification to link prediction. Here, we propose a method based on researchers’ institution affiliation for predicting links in a collaboration social network. Initial experiments show that considering the institution affiliation aspect, the set of recommendations is more accurate and concise, leading to a more efficient result.