Summary
Spreading processes, such as cascading failure of technological networks, epidemic outbreak and contagion in social
networks are ubiquitous and have a significant impact on the modern society. In many cases, transitions to large-scale
blackouts or global pandemics occur abruptly due to tiny changes in system parameters; epidemics and social movements
can spread out explosively, forming avalanche-like outbreaks in a very short period. The drastic transitions are beneficial for
making global impact of boosting charity campaigns and commercial advertising but can also have catastrophic
consequences when epidemics or failures spread to large part of a critical systems abruptly, without any early warning
signals. Moreover, multiple cooperative of competitive spreading processes make the picture even more complex.
Previous work in this area focused on the asymptotic manifestation of the process and typically ignored the interplay
between specific system topology and the dynamics. Methods to monitor, identify and control drastic transitions and
outbreaks in heterogeneous realistic networks are lacking. In this project, we will investigate the signs for abrupt transitions
and avalanche outbreaks both macroscopically and in specific instances, to gain insight into the conditions for their onset.
We will develop methods to contain (or facilitate) the outbreaks by optimal deployment of resources, such as applying
vaccines or distributing promotion material by employing the recently developed dynamic message passing techniques from
statistical physics. We will collaborate with British Telecom to promote product marketing and service provision by using the
new optimisation algorithms. This project will have significant impact on the scientific understanding of non-equilibrium
spreading processes, provide algorithmic solutions for practical problems in specific instances, will support policy making
decisions and offer optimal resource allocation for commercial marketing tasks.
networks are ubiquitous and have a significant impact on the modern society. In many cases, transitions to large-scale
blackouts or global pandemics occur abruptly due to tiny changes in system parameters; epidemics and social movements
can spread out explosively, forming avalanche-like outbreaks in a very short period. The drastic transitions are beneficial for
making global impact of boosting charity campaigns and commercial advertising but can also have catastrophic
consequences when epidemics or failures spread to large part of a critical systems abruptly, without any early warning
signals. Moreover, multiple cooperative of competitive spreading processes make the picture even more complex.
Previous work in this area focused on the asymptotic manifestation of the process and typically ignored the interplay
between specific system topology and the dynamics. Methods to monitor, identify and control drastic transitions and
outbreaks in heterogeneous realistic networks are lacking. In this project, we will investigate the signs for abrupt transitions
and avalanche outbreaks both macroscopically and in specific instances, to gain insight into the conditions for their onset.
We will develop methods to contain (or facilitate) the outbreaks by optimal deployment of resources, such as applying
vaccines or distributing promotion material by employing the recently developed dynamic message passing techniques from
statistical physics. We will collaborate with British Telecom to promote product marketing and service provision by using the
new optimisation algorithms. This project will have significant impact on the scientific understanding of non-equilibrium
spreading processes, provide algorithmic solutions for practical problems in specific instances, will support policy making
decisions and offer optimal resource allocation for commercial marketing tasks.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/835913 |
| Start date: | 01-08-2019 |
| End date: | 31-07-2021 |
| Total budget - Public funding: | 224 933,76 Euro - 224 933,00 Euro |
Cordis data
Original description
Spreading processes, such as cascading failure of technological networks, epidemic outbreak and contagion in socialnetworks are ubiquitous and have a significant impact on the modern society. In many cases, transitions to large-scale
blackouts or global pandemics occur abruptly due to tiny changes in system parameters; epidemics and social movements
can spread out explosively, forming avalanche-like outbreaks in a very short period. The drastic transitions are beneficial for
making global impact of boosting charity campaigns and commercial advertising but can also have catastrophic
consequences when epidemics or failures spread to large part of a critical systems abruptly, without any early warning
signals. Moreover, multiple cooperative of competitive spreading processes make the picture even more complex.
Previous work in this area focused on the asymptotic manifestation of the process and typically ignored the interplay
between specific system topology and the dynamics. Methods to monitor, identify and control drastic transitions and
outbreaks in heterogeneous realistic networks are lacking. In this project, we will investigate the signs for abrupt transitions
and avalanche outbreaks both macroscopically and in specific instances, to gain insight into the conditions for their onset.
We will develop methods to contain (or facilitate) the outbreaks by optimal deployment of resources, such as applying
vaccines or distributing promotion material by employing the recently developed dynamic message passing techniques from
statistical physics. We will collaborate with British Telecom to promote product marketing and service provision by using the
new optimisation algorithms. This project will have significant impact on the scientific understanding of non-equilibrium
spreading processes, provide algorithmic solutions for practical problems in specific instances, will support policy making
decisions and offer optimal resource allocation for commercial marketing tasks.
Status
CLOSEDCall topic
MSCA-IF-2018Update Date
28-04-2024
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