Suppressing Information Diffusion via Link Blocking in Temporal Networks

Xiuxiu Zhan, Alan Hanjalic, Huijuan Wang*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)
10 Downloads (Pure)


In this paper, we explore how to effectively suppress the diffusion of (mis)information via blocking/removing the temporal contacts between selected node pairs. Information diffusion can be modelled as, e.g., an SI (Susceptible-Infected) spreading process, on a temporal social network: an infected (information possessing) node spreads the information to a susceptible node whenever a contact happens between the two nodes. Specifically, the link (node pair) blocking intervention is introduced for a given period and for a given number of links, limited by the intervention cost. We address the question: which links should be blocked in order to minimize the average prevalence over time? We propose a class of link properties (centrality metrics) based on the information diffusion backbone [19], which characterizes the contacts that actually appear in diffusion trajectories. Centrality metrics of the integrated static network have also been considered. For each centrality metric, links with the highest values are blocked for the given period. Empirical results on eight temporal network datasets show that the diffusion backbone based centrality methods outperform the other metrics whereas the betweenness of the static network, performs reasonably well especially when the prevalence grows slowly over time.

Original languageEnglish
Title of host publicationComplex Networks and Their Applications VIII
Subtitle of host publicationProceedings of the 8th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2019
EditorsHocine Cherifi, Sabrina Gaito, José Fernendo Mendes, Esteban Moro, Luis Mateus Rocha
Place of PublicationCham
Number of pages11
ISBN (Electronic)978-3-030-36687-2
ISBN (Print)978-3-030-36686-5
Publication statusPublished - 2020
Event COMPLEX NETWORKS 2019: 8th International Conference on Complex Networks and their Applications - Lisbon, Portugal
Duration: 10 Dec 201912 Dec 2019
Conference number: 8th

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503


Conference COMPLEX NETWORKS 2019

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Information diffusion backbone
  • Link blocking
  • Link centrality
  • SI spreading
  • Temporal network


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