socialrank algorithm based on hierarchy metric as defined in "Finding Hierarchy in Directed Online Social Networks" WWW 2012 paper
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README.md
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generate_subgraph.py
rewire.py
socialrank
socialrank.cpp
socialrank.py
www2011.bib

README.md

socialrank

Implementation of SocialRank algorithm.

SocialRank is an algorithm for finding the amount of hierarchy in a directed social network, and ranking nodes based on their level in this hierarchy.

SocialRank is based on the premise that the existence of a link indicates a social rank recommendation; a link u -> v (i.e. u is a follower of v) indicates a social recommendation of v from u. If there is no reverse link from v to u, it might indicate that v is higher up in the hierarchy than u. We assume that in social networks, when people connect to other people who are lower in the hierarchy, this causes them social agony. To infer the ranks of the nodes in the network, we find the best possible ranking, i.e. the ranking that gives the least social agony.

Based on publication: Finding Hierarchy in Directed Online Social Networks Mangesh Gupte, Pravin Shankar, Jing Li, S Muthukrishnan, Liviu Iftode. In the Proceedings of the 20th International World Wide Web Conference (WWW 2011), March 2011.

URL: http://paul.rutgers.edu/~spravin/www11_socialhierarchy.pdf

If you find this code useful, and use it in a publication, please cite the above paper. The bibtex entry is available at www2011.bib