Influence, originality and similarity in directed acyclic graphs
Physics and Society
2011-10-10 v1 Digital Libraries
Social and Information Networks
Abstract
We introduce a framework for network analysis based on random walks on directed acyclic graphs where the probability of passing through a given node is the key ingredient. We illustrate its use in evaluating the mutual influence of nodes and discovering seminal papers in a citation network. We further introduce a new similarity metric and test it in a simple personalized recommendation process. This metric's performance is comparable to that of classical similarity metrics, thus further supporting the validity of our framework.
Keywords
Cite
@article{arxiv.1108.3691,
title = {Influence, originality and similarity in directed acyclic graphs},
author = {Stanislao Gualdi and Matus Medo and Yi-Cheng Zhang},
journal= {arXiv preprint arXiv:1108.3691},
year = {2011}
}
Comments
6 pages, 4 figures