Month: April 2020

Improving the Robustness of Online Social Networks: A Simulation Approach of Network Interventions

Giona Casiraghi and Frank Schweitzer

Front. Robot. AI, 28 April 2020


Online social networks (OSN) are prime examples of socio-technical systems in which individuals interact via a technical platform. OSN are very volatile because users enter and exit and frequently change their interactions. This makes the robustness of such systems difficult to measure and to control. To quantify robustness, we propose a coreness value obtained from the directed interaction network. We study the emergence of large drop-out cascades of users leaving the OSN by means of an agent-based model. For agents, we define a utility function that depends on their relative reputation and their costs for interactions. The decision of agents to leave the OSN depends on this utility. Our aim is to prevent drop-out cascades by influencing specific agents with low utility. We identify strategies to control agents in the core and the periphery of the OSN such that drop-out cascades are significantly reduced, and the robustness of the OSN is increased.


Thermodynamics 2.0 | International Conference

June 22-24, 2020


The International Conference on Thermodynamics 2.0, ICT2.0 in short, is all about coevolution of sciences – identifying and connecting dots of scientific revolutions in natural and social sciences.

ICT2.0 aims to empower science, engineering and humanity. A short-term objective of ICT2.0 is a blueprint of bridge between two cultures commonly referred to as natural science and social science.


Population flow drives spatio-temporal distribution of COVID-19 in China

Sudden, large-scale, and diffuse human migration can amplify localized outbreaks into widespread epidemics.1–4 Rapid and accurate tracking of aggregate population flows may therefore be epidemiologically informative. Here, we use mobile-phone-data-based counts of 11,478,484 people egressing or transiting through the prefecture of Wuhan between 1 January and 24 January 2020 as they moved to 296 prefectures throughout China. First, we document the efficacy of quarantine in ceasing movement. Second, we show that the distribution of population outflow from Wuhan accurately predicts the relative frequency and geographic distribution of COVID-19 infections through February 19, 2020, across all of China. Third, we develop a spatio-temporal “risk source” model that leverages population flow data (which operationalizes risk emanating from epidemic epicenters) to not only forecast confirmed cases, but also to identify high-transmission-risk locales at an early stage. Fourth, we use this risk source model to statistically derive the geographic spread of COVID-19 and the growth pattern based on the population outflow from Wuhan; the model yields a benchmark trend and an index for assessing COVID-19 community transmission risk over time for different locations. This approach can be used by policy-makers in any nation with available data to make rapid and accurate risk assessments and to plan allocation of limited resources ahead of ongoing outbreaks.


Jayson S. Jia, Xin Lu, Yun Yuan, Ge Xu, Jianmin Jia & Nicholas A. Christakis 
Nature (2020)


Pandemics, Modelling, and Policy – Massive Open Online Course

Discover the role forecasts and computer models play in understanding pandemics

With the world in the grip of the coronavirus pandemic, there has been a surge of interest in scientific modelling of the outbreak.

On this course, you’ll explore the social, economic, and political factors in the spread of a pandemic such as COVID-19, examining how scientists try to forecast the spread and severity of epidemics, and what we can and can’t know.

You’ll use interactive graphical programs to explore the dynamics of epidemics, learning how to critique the underlying models, and how science and computer models can support policymakers in times of pandemic crisis.


Tenth International Conference on Complex Systems — ICCS 2020 will be an online event.

Due to the ongoing COVID-19 outbreak, the Executive Committee has made the decision to move ICCS 2020 to an online-only event.

While the outlook for the unprecedented challenges we are facing from COVID-19 remain uncertain, our values are clearer than ever. The health and safety of our communities—academic, local, and business—are of the utmost priority. Further, we know as complex systems scientists that we must play our part by endeavoring to fragment our physical contact networks, yet strengthen our virtual social networks. We also remain committed to the pursuit of creating and sharing knowledge, and wish to honor our promise to provide a rich forum in which to do this. It is with these tenets in mind that we made the decision to make ICCS 2020 a 100% online-only event.

What you need to know:

  • The dates remain the same: July 26th – July 31st 2020

  • Registration has reopened, but If you have already registered for the live event, we will soon be contacting you directly with more details and information on refunds

  • We encourage you to continue submitting abstracts or papers on EasyChair

  • …especially if your work relates to COVID-19.

We are excited to rise to the occasion of conducting a large conference virtually and look forward to “seeing” you all in July! If you have any questions, we encourage you to get in touch:

To see what NECSI is doing to combat the outbreak and to learn more about how you can protect yourself, your family and your community, go to: