Ego-net Analysis of Co-authorship Networks

Abstract

This thesis tries to analyze academic networks attained from research papers, in particular co-author networks, have been studied widely. The ego-net analysis towards co-authorship networks, which helps in analyzing the separate individual actors (or authors) and their coauthors which is the sole purpose of this approach rather than analyzing as such full cluster all together. In DBLP dataset, where each author’s publications who has correlated with other authors are very larger and diffuse, excluding individual publications. We will visualize selective author networks based on the interactions with others and study about various measurements of ego networks where the first order neighborhood of the node(author) is selected which helps to attain knowledge about every individual, as well as the characteristics they hold.