An implementation of the absorbing random-walk centrality measure for graphs.

graph, mining, node, centrality, random, walks, algorithms, data
pip install absorbing_centrality==0.1.0


Absorbing Random-Walk Centrality

Documentation Statu Travis-CI Build Status Coverage Status

This is an implementation of the absorbing random-walk centrality measure for nodes in graphs. For the definition of the measure, as well as a study of the related optimization problem and algorithmic techniques, please see the pre-print publication on arXiv. A short version of this paper will appear in the ICDM 2015.

To cite this work, please use

Mavroforakis, Charalampos, Michael Mathioudakis, and Aristides Gionis.
"Absorbing random-walk centrality: Theory and algorithms"
Data Mining (ICDM), 2015 IEEE International Conference on. IEEE, 2015.


You can install the absorbing_centrality package by executing the following command in a terminal.

pip install absorbing_centrality


For instructions on how to use the package, consult its documentation.


You can find an example of how to use this package in this IPython notebook.


To run all the tests for the code, you will need tox -- check its webpage for instructions on how to install it.

Once tox is installed, use your terminal to enter the directory with the local copy of the code (here it's named 'absorbing-centrality') and simply type the following command.

absorbing-centrality $ tox

If everything goes well, you'll receive a congratulatory message.

Note that the code is distributed under the Open Source Initiative (ISC) license. For the exact terms of distribution, see the LICENSE.

Copyright (c) 2015, absorbing-centrality contributors,
Charalampos Mavroforakis <cmav@bu.edu>,
Michael Mathioudakis <michael.mathioudakis@aalto.fi>,
Aristides Gionis <aristides.gionis@aalto.fi>