Investigating Negative Interactions in Multiplex Networks: A Mutual Information Approach release_exuercwzprdkzkg2ylmlksyfqi

by Alireza Hajibagheri, Gita Sukthankar

Released as a article .

2018  

Abstract

Many interesting real-world systems are represented as complex networks with multiple types of interactions and complicated dependency structures between layers. These interactions can be encoded as having a valence with positive links marking interactions such as trust and friendship and negative links denoting distrust or hostility. Extracting information from these negative interactions is challenging since standard topological metrics are often poor predictors of negative link formation, particularly across network layers. In this paper, we introduce a method based on mutual information which enables us to predict both negative and positive relationships. Our experiments show that SMLP (Signed Multiplex Link Prediction) can leverage negative relationship layers in multiplex networks to improve link prediction performance.
In text/plain format

Archived Files and Locations

application/pdf  940.5 kB
file_lvbgo6hh4jawjmcy52ca5rkqwi
arxiv.org (repository)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article
Stage   submitted
Date   2018-04-24
Version   v2
Language   en ?
arXiv  1804.07210v2
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 24e605c6-16d8-4616-831b-02707425dedf
API URL: JSON