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1. A Framework for Simulating Multiple Contagions Over Multiple Networks

   https://doi.org/10.1007/978-3-030-93413-2_21  

   Kishore, Aparna ; Machi, Lucas ; Kuhlman, Chris J ; Machi, Dustin ; Ravi, S S. ( January 2021 , Complex Networks and their Applications)

   Many contagion processes evolving on populations do so simultaneously, interacting over time. Examples are co-evolution of human social processes and diseases, such as the uptake of mask wearing and disease spreading. Commensurately, multi-contagion agent-based simulations (ABSs) that represent populations as networks in order to capture interactions between pairs of nodes are becoming more popular. In this work, we present a new ABS system that simulates any number of contagions co-evolving on any number of networked populations. Individual (interacting) contagion models and individual networks are specified, and the system computes multi-contagion dynamics over time. This is a significant improvement over simulationmore »frameworks that require union graphs to handle multiple networks, and/or additional code to orchestrate the computations of multiple contagions. We provide a formal model for the simulation system, an overview of the software, and case studies that illustrate applications of interacting contagions.« less
2. Influence Propagation with Multiple Stages over Random Multiplex Networks

   https://doi.org/10.1109/GLOBECOM38437.2019.9013531  

   Zhuang, Yong ; Yagan, Osman ( December 2019 , 2019 IEEE Global Communications Conference (GLOBECOM))

   Complex contagion models have been developed to understand a wide range of social phenomena such as adoption of cultural fads, the diffusion of belief, norms, and innovations in social networks, and the rise of collective action to join a riot. Most existing works focus on contagions where individuals’ states are represented by binary variables, and propagation takes place over a single isolated network. However, characterization of an individual’s standing on a given matter as a binary state might be overly simplistic as most of our opinions, feelings, and perceptions vary over more than two states. Also, most real-world contagions takemore »place over multiple networks (e.g., Twitter and Facebook) or involve multiplex networks where individuals engage in different types of relationships (e.g., co-worker, family, etc.). To this end, this paper studies multi-stage complex contagions that take place over multi-layer or multiplex networks. Under a linear threshold based contagion model, we first give analytic results for the expected size of global cascades, i.e., cases where a randomly chosen node can initiate a propagation that eventually reaches a positive fraction of the whole population. Then, analytic results are confirmed by an extensive numerical study. In addition, we demonstrate how the dynamics of complex contagions is affected by the structural properties of the networks. In particular, we reveal an interesting connection between the assortativity of a network and the impact of hyper-active nodes on the cascade size.« less
3. Diffusion in Social Networks: Effects of Monophilic Contagion, Friendship Paradox and Reactive Networks

   https://doi.org/10.1109/TNSE.2019.2909015  

   Nettasinghe, Buddhika ; Krishnamurthy, Vikram ; Lerman, Kristina ( April 2019 , IEEE Transactions on Network Science and Engineering)

   We consider SIS contagion processes over networks where, a classical assumption is that individuals' decisions to adopt a contagion are based on their immediate neighbors. However, recent literature shows that some attributes are more correlated between two-hop neighbors, a concept referred to as monophily. This motivates us to explore monophilic contagion, the case where a contagion (e.g. a product, disease) is adopted by considering two-hop neighbors instead of immediate neighbors (e.g. you ask your friend about the new iPhone and she recommends you the opinion of one of her friends). We show that the phenomenon called friendship paradox makes itmore »easier for the monophilic contagion to spread widely. We also consider the case where the underlying network stochastically evolves in response to the state of the contagion (e.g. depending on the severity of a flu virus, people restrict their interactions with others to avoid getting infected) and show that the dynamics of such a process can be approximated by a differential equation whose trajectory satisfies an algebraic constraint restricting it to a manifold. Our results shed light on how graph theoretic consequences affect contagions and, provide simple deterministic models to approximate the collective dynamics of contagions over stochastic graph processes.« less
4. Blocking the Propagation of Two Simultaneous Contagions over Networks

   Carscadden, H ; Kuhlman, C ; Marathe, M ; Ravi, SS ; Rosenkrantz, D ( December 2020 , International conference on complex networks and their applications)

   We consider the simultaneous propagation of two contagions over a social network. We assume a threshold model for the propagation of the two contagions and use the formal framework of discrete dynamical systems. In particular, we study an optimization problem where the goal is to minimize the total number of infected nodes subject to a budget constraint on the total number of nodes that can be vaccinated. While this problem has been considered in the literature for a single contagion, our work considers the simultaneous propagation of two contagions. Since the optimization problem is NP-hard, we develop a heuristic basedmore »on a generalization of the set cover problem. Using experiments on three real-world networks, we compare the performance of the heuristic with some baseline methods.« less
5. Blocking the Propagation of Two Simultaneous Contagions over Networks

   Carscadden, Henry L ; Kuhlman, Chris J ; Marathe, Madhav V ; Ravi, S S ; Rosenkrantz, Daniel J ( January 2020 , International Conference on Complex Networks and their Applications (Complex Networks))

   We consider the simultaneous propagation of two contagions over a social network. We assume a threshold model for the propagation of the two contagions and use the formal framework of discrete dynamical systems. In particular, we study an optimization problem where the goal is to minimize the total number of infected nodes subject to a budget constraint on the total number of nodes that can be vaccinated. While this problem has been considered in the literature for a single contagion, our work considers the simultaneous propagation of two contagions. Since the optimization problem is NP-hard, we develop a heuristic basedmore »on a generalization of the set cover problem. Using experiments on three real-world networks, we compare the performance of the heuristic with some baseline methods.« less