Are social bots a real threat? An agent-based model of the spiral of silence to analyse the impact of manipulative actors in social networks

2019 ◽  
Vol 28 (4) ◽  
pp. 394-412 ◽  
Author(s):  
Björn Ross ◽  
Laura Pilz ◽  
Benjamin Cabrera ◽  
Florian Brachten ◽  
German Neubaum ◽  
...  
2020 ◽  
Author(s):  
Giuseppe Giacopelli

UNSTRUCTURED COVID-19 outbreak is an awful event. However it gives to the scientists the possibility to test theories about epidemic. The aim of this contribution is to propose a individual-based model of Lombardy COVID-19 outbreak at full-scale, where full-scale means that will be simulated all the 10 millions inhabitant population of Lombardy person by person, in a commercial computer. All this to test the impact of our daily actions in epidemic, investigate social networks connectivity and in the end have an insight on the impact of an hypothetical vaccine.


2020 ◽  
Author(s):  
Giuseppe Giacopelli

COVID-19 outbreak is an awful event. However it gives to the scientists the possibility to test theories about epidemic. The aim of this contribution is to propose a individual-based model of Lombardy COVID-19 outbreak at full-scale, where full-scale means that will be simulated all the 10 millions inhabitant population of Lombardy person by person, in a commercial computer. All this to test the impact of our daily actions in epidemic, investigate social networks connectivity and in the end have an insight on the impact of an hypothetical vaccine.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.


2014 ◽  
Vol 104 (7) ◽  
pp. 1196-1203 ◽  
Author(s):  
Yong Yang ◽  
Ana Diez-Roux ◽  
Kelly R. Evenson ◽  
Natalie Colabianchi

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