A basic problem in the analysis of social networks is missing data. When a
network model does not accurately capture all the actors or relationships in
the social system under study, measures computed on the network and ultimately
the final outcomes of the analysis can be severely distorted. For this reason,
researchers in social network analysis have characterised the impact of
different types of missing data on existing network measures. Recently a lot of
attention has been devoted to the study of multiple-network systems, e.g.,
multiplex networks. In these systems missing data has an even more significant
impact on the outcomes of the analyses. However, to the best of our knowledge,
no study has focused on this problem yet. This work is a first step in the
direction of understanding the impact of missing data in multiple networks. We
first discuss the main reasons for missingness in these systems, then we
explore the relation between various types of missing information and their
effect on network properties. We provide initial experimental evidence based on
both real and synthetic data.
%0 Conference Paper
%1 Sharma2014Missing
%A Sharma, Rajesh
%A Magnani, Matteo
%A Montesi, Danilo
%B 2014 Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
%D 2014
%I IEEE
%K multiplex-networks missing-data
%P 401--407
%R 10.1109/SITIS.2014.65
%T Missing Data in Multiplex Networks: A Preliminary Study
%U http://dx.doi.org/10.1109/SITIS.2014.65
%X A basic problem in the analysis of social networks is missing data. When a
network model does not accurately capture all the actors or relationships in
the social system under study, measures computed on the network and ultimately
the final outcomes of the analysis can be severely distorted. For this reason,
researchers in social network analysis have characterised the impact of
different types of missing data on existing network measures. Recently a lot of
attention has been devoted to the study of multiple-network systems, e.g.,
multiplex networks. In these systems missing data has an even more significant
impact on the outcomes of the analyses. However, to the best of our knowledge,
no study has focused on this problem yet. This work is a first step in the
direction of understanding the impact of missing data in multiple networks. We
first discuss the main reasons for missingness in these systems, then we
explore the relation between various types of missing information and their
effect on network properties. We provide initial experimental evidence based on
both real and synthetic data.
%@ 978-1-4799-7978-3
@inproceedings{Sharma2014Missing,
abstract = {{A basic problem in the analysis of social networks is missing data. When a
network model does not accurately capture all the actors or relationships in
the social system under study, measures computed on the network and ultimately
the final outcomes of the analysis can be severely distorted. For this reason,
researchers in social network analysis have characterised the impact of
different types of missing data on existing network measures. Recently a lot of
attention has been devoted to the study of multiple-network systems, e.g.,
multiplex networks. In these systems missing data has an even more significant
impact on the outcomes of the analyses. However, to the best of our knowledge,
no study has focused on this problem yet. This work is a first step in the
direction of understanding the impact of missing data in multiple networks. We
first discuss the main reasons for missingness in these systems, then we
explore the relation between various types of missing information and their
effect on network properties. We provide initial experimental evidence based on
both real and synthetic data.}},
added-at = {2019-06-10T14:53:09.000+0200},
archiveprefix = {arXiv},
author = {Sharma, Rajesh and Magnani, Matteo and Montesi, Danilo},
biburl = {https://www.bibsonomy.org/bibtex/24ccd3134634330285f30622c3b89206f/nonancourt},
booktitle = {2014 Tenth International Conference on Signal-Image Technology \& Internet-Based Systems (SITIS)},
citeulike-article-id = {13378256},
citeulike-linkout-0 = {http://dx.doi.org/10.1109/SITIS.2014.65},
citeulike-linkout-1 = {http://arxiv.org/abs/1409.7623},
citeulike-linkout-2 = {http://arxiv.org/pdf/1409.7623},
day = 26,
doi = {10.1109/SITIS.2014.65},
eprint = {1409.7623},
interhash = {5fdcfc1d0b853955925fa9d564c71fd7},
intrahash = {4ccd3134634330285f30622c3b89206f},
isbn = {978-1-4799-7978-3},
keywords = {multiplex-networks missing-data},
location = {Marrakech, Morocco},
month = nov,
pages = {401--407},
posted-at = {2014-09-30 09:27:30},
priority = {2},
publisher = {IEEE},
timestamp = {2019-08-22T16:27:38.000+0200},
title = {{Missing Data in Multiplex Networks: A Preliminary Study}},
url = {http://dx.doi.org/10.1109/SITIS.2014.65},
year = 2014
}