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The detection of influential nodes in a social network is an active researcharea with many valuable applications including marketing and advertisement. Asa new application in academia, KDD Cup 2016 shed light on the lack of anexisting objective ranking for institutions within their respective researchareas and proposed a solution for it. In this problem, the academic fields aredefined as social networks whose nodes are the active institutions within thefield, with the most influential nodes representing the highest contributors.The solution is able to provide a ranking of active institutions within theirspecific domains. The problem statement provided an annual scoring mechanismfor institutions based on their publications and encouraged the use of anypublicly available dataset such as the Microsoft Academic Graph (MAG). Thecontest was focused on research publications in selected conferences and askedfor a prediction of the ranking for active institutions within thoseconferences in 2016. It should be noted that the results of the papersubmissions and therefore the ground truths for KDD Cup were unknown at thetime of the contest. Each team's final ranking list was evaluated by a metriccalled NDCG@20 after the results were released. This metric was used toindicate the distance between each team's proposed ranking and the actual oneonce it was known. After computing the scores of institutions for each yearstarting from 2011, we aggregated the rankings by summing the normalized scoresacross the years and using the final score set to provide the final ranking.Since the 2016 ground truths were unknown, we utilized the scores from2011-2014 and used the 2015 publications as a test bed for evaluating ouraggregation method. Based on the testing, summing the normalized scores got usclosest to the actual 2015 rankings and using same heuristic for predicting the2016 results.

Ranking Research Institutions Based On Related Academic Conferences