Scientometrics for Success and Influence in the Microsoft Academic Graph

摘要

Measuring and evaluating an author's impact has been a withstanding challenge in the academic world with profound effects on society. Apart from its practical usage for academic evaluation, it enhances transparency and reinforces scientific excellence. In this demo paper we present our efforts to address this problem capitalizing on the field-based citations and the author oriented citation network extracted from the Microsoft Academic Graph, to our knowledge the largest network of its kind. We separate impact into two dimensions: success and influence over the network, and provide two novel scientometrics to quantify some of their aspects: (i) the distribution of the h-index for specific scientific fields and a search engine to visualize an authors' position in it as well as the top percentile she belongs to, (ii) recomputing our previously introduced D-core influence metric on this huge network and presenting authority/integration of the authors in the form of D-core frontiers. In addition we present interesting insights on the most dense scientific domains and the most influential authors. We believe the proposed analytics highlight under-examined aspects in the area of scientific evaluation and pave the way for more involved scientometrics.