Sir Model for Fake News Spreading Through Whatsapp

2018 ◽  
Author(s):  
Pooja Khurana ◽  
Deepak Kumar
Keyword(s):  
Sir Model ◽  
Fake News

scholarly journals Stiffness Analysis to Predict the Spread Out of Fake Information

2021 ◽  
Vol 13 (9) ◽  
pp. 222
Author(s):  
Raffaele D'Ambrosio ◽  
Giuseppe Giordano ◽  
Serena Mottola ◽  
Beatrice Paternoster
Keyword(s):  
Numerical Experiments ◽  
Real Data ◽  
Sir Model ◽  
Stiffness Index ◽  
Fake News ◽  
Stiffness Analysis ◽  
Data Support

This work highlights how the stiffness index, which is often used as a measure of stiffness for differential problems, can be employed to model the spread of fake news. In particular, we show that the higher the stiffness index is, the more rapid the transit of fake news in a given population. The illustration of our idea is presented through the stiffness analysis of the classical SIR model, commonly used to model the spread of epidemics in a given population. Numerical experiments, performed on real data, support the effectiveness of the approach.

scholarly journals Protection Strategy for Edge-Weighted Graphs in Disease Spread

2021 ◽  
Vol 11 (11) ◽  
pp. 5115
Author(s):  
Ronald Manríquez ◽  
Camilo Guerrero-Nancuante ◽  
Carla Taramasco
Keyword(s):  
Infectious Disease ◽  
Weighted Graph ◽  
Sir Model ◽  
Disease Spread ◽  
Weighted Graphs ◽  
Fake News ◽  
Scale Free ◽  
Protection Strategy ◽  
Immunization Strategies ◽  
Scale Free Networks

Fake news, viruses on computer systems or infectious diseases on communities are some of the problems that are addressed by researchers dedicated to study complex networks. The immunization process is the solution to these challenges and hence the importance of obtaining immunization strategies that control these spreads. In this paper, we evaluate the effectiveness of the DIL-Wα ranking in the immunization of nodes that are attacked by an infectious disease that spreads on an edge-weighted graph using a graph-based SIR model. The experimentation was done on real and scale-free networks and the results illustrate the benefits of this ranking.

Maier-Kolumne – Fake News

physiopraxis ◽  
2018 ◽  
Vol 16 (07/08) ◽  
pp. 58-58
Author(s):  
Ulrike Maier
Keyword(s):  
Fake News

Eine Hausärztin, die, statt ein Physio-Rezept auszustellen, auf Übungen aus der Apotheken Umschau verweist? Unmöglich, sollte man meinen. Doch Physiotherapeutin Ulrike Maier belehrt eines Besseren. Ihre unwissende Hausärztin von nebenan liefert ihren Patienten gerne mal „alternative Fakten“ und hat bei ihren physiotherapeutischen Kenntnissen noch dringend Nachholbedarf.

Datos masivos, algoritmización y nuevos medios frente a desinformación y fake news. Bots para minimizar el impacto en las organizaciones

2020 ◽  
pp. 101-114
Author(s):  
Jesús Miguel Flores Vivar
Keyword(s):  
Fake News

Éste trabajo parte de una información compartida por muchos investigadores. La comprensión de la desinformación como un fenómeno que va mucho más allá del término “noticias falsas”. Estos términos han sido apropiados y usados engañosamente por poderosos actores para desestimar y poner en entredicho la cobertura informativa que ya atraviesa momentos críticos sobre la credibilidad.

Says Who? The Effects of Presentation Format and Source Rating on Fake News in Social Media

MIS Quarterly ◽  
2019 ◽  
Vol 43 (3) ◽  
pp. 1025-1039 ◽  
Author(s):  
Antino Kim ◽  
◽  
Alan R. Dennis ◽  
Keyword(s):  
Social Media ◽  
Presentation Format ◽  
Fake News
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