@inproceedings{796f9f8e7283489abb8ea20b506f7e74,
title = "How even tiny influence can have a big impact!",
abstract = "An influence network is a graph where each node changes its state according to a function of the states of its neighbors. We present bounds for the stabilization time of such networks. We derive a general bound for the classic {"}Democrats and Republicans{"} problem and study different model modifications and their influence on the way of stabilizing and their stabilization time. Our main contribution is an exponential lower and upper bound on weighted influence networks. We also investigate influence networks with asymmetric weights and show an influence network with an exponential cycle length in the stable situation.",
keywords = "Asymmetric Graphs, Equilibrium, Influence Networks, Majority Function, Social Networks, Stabilization, Weighted Graphs",
author = "Barbara Keller and David Peleg and Roger Wattenhofer",
year = "2014",
doi = "10.1007/978-3-319-07890-8_22",
language = "אנגלית",
isbn = "9783319078892",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "252--263",
booktitle = "Fun with Algorithms - 7th International Conference, FUN 2014, Proceedings",
address = "גרמניה",
note = "7th International Conference on Fun with Algorithms, FUN 2014 ; Conference date: 01-07-2014 Through 03-07-2014",
}