Award Abstract # 2225513
CIF: Small: Modeling, Analysis, and Control of Contagion Processes in Networks

NSF Org: CCF
Division of Computing and Communication Foundations
Recipient: CARNEGIE MELLON UNIVERSITY
Initial Amendment Date: July 14, 2022
Latest Amendment Date: July 14, 2022
Award Number: 2225513
Award Instrument: Standard Grant
Program Manager: Phillip Regalia
pregalia@nsf.gov
 (703)292-2981
CCF
 Division of Computing and Communication Foundations
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2022
End Date: September 30, 2026 (Estimated)
Total Intended Award Amount: $600,000.00
Total Awarded Amount to Date: $600,000.00
Funds Obligated to Date: FY 2022 = $600,000.00
History of Investigator:
  • Osman Yagan (Principal Investigator)
    oyagan@ece.cmu.edu
Recipient Sponsored Research Office: Carnegie-Mellon University
5000 FORBES AVE
PITTSBURGH
PA  US  15213-3890
(412)268-8746
Sponsor Congressional District: 12
Primary Place of Performance: Carnegie-Mellon University
5000 FORBES AVE
PITTSBURGH
PA  US  15213-3815
Primary Place of Performance
Congressional District:
12
Unique Entity Identifier (UEI): U3NKNFLNQ613
Parent UEI: U3NKNFLNQ613
NSF Program(s): Comm & Information Foundations
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7923, 7937
Program Element Code(s): 779700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Contagion processes such as propagation of influence, information, and viruses can have dramatic impacts on the health and well-being of the society. This project will reveal how contagions are affected by various factors and parameters, some of which can be controlled by public-policy measures and by adjusting individuals? behaviors. Thus, the project can help in developing efficient mechanisms for mitigating large-scale contagions including infectious-disease pandemics and misinformation campaigns. The project can also have a positive impact on national security by providing an improved understanding of the role of social influence in shaping popular opinion and actions, and thereby an improved capability to predict and control spread of antisocial behavior. The team of researchers will incorporate project results in teaching and disseminate them broadly in academic and industrial venues. The project will involve women and minority students and will include extensive outreach to K-12 students and teachers.

This project aims to develop new approaches in modeling, analysis, and control of simple (e.g., spread of information and diseases) and complex contagions (e.g., spread of influence and opinions) over networks. First, a novel complex contagion model will be used to study the simultaneous spread of multiple correlated opinions. Utilizing this model, the team of researchers will i) derive fundamental relations between the network topology, the correlations among opinions, and the propagation dynamics including final fraction of individuals supporting each opinion; ii) reveal the impact of correlated opinion propagation on the polarization in the population; and iii) develop algorithms to efficiently control the spread of an opinion with constraints on other opinions and/or polarization. For simple contagions, the team of researchers will analyze novel models of both information and viral spread and reveal the impact of i) mutations in the spreading item; and ii) the heterogeneity in the population, e.g., due to different mask-wearing behavior, vaccination status, or socio-cultural diversity, on the contagion dynamics.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Murdock, Isabel and Carley, Kathleen M and Yaan, Osman "An Agent-Based Model of Reddit Interactions and Moderation" , 2023 https://doi.org/10.1145/3625007.3627489 Citation Details
Murdock, Isabel and Carley, Kathleen M. and Yaan, Osman "Identifying cross-platform user relationships in 2020 U.S. election fraud and protest discussions" Online Social Networks and Media , v.33 , 2023 https://doi.org/10.1016/j.osnem.2023.100245 Citation Details
Sood, Mansi and Eletreby, Rashad and Kumar, Swarun and Wu, Chai Wah and Yaan, Osman "The Interplay of Clustering and Evolution in the Emergence of Epidemics on Networks" IEEE International Conference on Communications , 2023 https://doi.org/10.1109/ICC45041.2023.10279814 Citation Details
Sood, Mansi and Sridhar, Anirudh and Eletreby, Rashad and Wu, Chai Wah and Levin, Simon A. and Yaan, Osman and Poor, H. Vincent "Spreading processes with mutations over multilayer networks" Proceedings of the National Academy of Sciences , v.120 , 2023 https://doi.org/10.1073/pnas.2302245120 Citation Details
Tian, Yurun and Sridhar, Anirudh and Wu, Chai Wah and Levin, Simon A. and Carley, Kathleen M. and Poor, H. Vincent and Yaan, Osman "Role of masks in mitigating viral spread on networks" Physical Review E , v.108 , 2023 https://doi.org/10.1103/PhysRevE.108.014306 Citation Details
Tian, Yurun and Yaan, Osman "Multi-Dimensional Threshold Model With Correlation: Emergence of Global Cascades" , 2024 https://doi.org/10.1109/ICC51166.2024.10622572 Citation Details
Tian, Yurun and Yaan, Osman "Spreading Processes With Layer-Dependent Population Heterogeneity Over Multilayer Networks" IEEE Transactions on Network Science and Engineering , v.11 , 2024 https://doi.org/10.1109/TNSE.2024.3396730 Citation Details
Tian, Yurun and Yaan, Osman "Spreading Processes with Population Heterogeneity Over Multi-Layer Networks" , 2023 https://doi.org/10.1109/GLOBECOM54140.2023.10437832 Citation Details

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