Structures and Statistics of Citation Networks

Abstract

The growing of availability of electronic resources over the Internet enables rapid dissemination of the ideas and changes in the trends and the interaction patterns. In this work, we focus on dynamic, evolving social networks which exhibit numerous features that are also of interest to many researchers in nonsocial fields such as statistical physics, biology, applied mathematics, and computer science. We investigate how a specific research area (high-energy physics) changes over time, by building interlinked citation, publication, and co-publication networks that evolve and expand constantly through the emergence of new papers and authors. More specifically, following an interdisciplinary approach, we analyze the dataset in its full and reduced forms using techniques that are borrowed from social networks (key author/paper analysis), spatial analysis (relationship among involved countries), statistical physics (investigation of power laws in citation/authorship networks), and text mining (investigation of scientific breakthroughs). We also show how techniques such as Fourier analysis that are of particular interest to electrical engineers find their place in this interdisciplinary approach. With this kind of comprehensive analysis, we aim to answer questions like: Who are the key authors (researchers) in this field of research? from them? What do the topological features of citation/collaboration networks tell us? What can we learn What kinds of over-time trends are observed in these networks? How often do authors publish? collaborate? Which organizations/cities/countries are involved in this research? How often do certain countries How can we use text contents to detect scientific breakthroughs? 1