DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Global and local community memberships for estimating spreading capability of nodes in social networks

Krukowski, Simon and Hecking, Tobias (2021) Global and local community memberships for estimating spreading capability of nodes in social networks. Applied Network Science, 6 (84). Springer Nature. doi: 10.1007/s41109-021-00421-3. ISSN 2364-8228.

[img] PDF - Published version

Official URL: https://appliednetsci.springeropen.com/articles/10.1007/s41109-021-00421-3


The analysis of spreading processes within complex networks can offer many important insights for the application in contexts such as epidemics, information dissemination or rumours. Particularly, structural factors of the network which either contribute or hinder the spreading are of interest, as they can be used to control or predict such processes. In social networks, the community structure is especially relevant, as actors usually participate in different densely connected social groups which emerge from various contexts, potentially allowing them to inject the spreading process into many different communities quickly. This paper extends our recent findings on the community membership of nodes and how it can be used to predict their individual spreading capability (Krukowski & Hecking, 2020) by further evaluating it on additional networks (both real-world networks and artificially generated networks), while additionally introducing a new local measure to identify influential spreaders that—in contrast to most other measures, does not rely on knowledge of the global network structure. The results confirm our recent findings, showing that the community membership of nodes can be used as a predictor for their spreading capability, while also showing that especially the local measure proves to be a good predictor, effectively outperforming the global measure in many cases. The results are discussed with regard to real-world use cases, where knowledge of the global structure is often not given, yet a prediction regarding the spreading capability highly desired (e.g., contact-tracing apps).

Item URL in elib:https://elib.dlr.de/145115/
Document Type:Article
Title:Global and local community memberships for estimating spreading capability of nodes in social networks
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hecking, TobiasUNSPECIFIEDhttps://orcid.org/0000-0003-0833-7989
Journal or Publication Title:Applied Network Science
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Publisher:Springer Nature
Keywords:Social Netzwork Analysis, Spreading Processes on Networks, Network Science
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Tasks SISTEC
Location: Köln-Porz
Institutes and Institutions:Institute for Software Technology
Institute for Software Technology > Intelligent and Distributed Systems
Deposited By: Hecking, Tobias
Deposited On:22 Nov 2021 13:37
Last Modified:29 Nov 2021 10:37

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.