1,934 research outputs found
Spreading processes in Multilayer Networks
Several systems can be modeled as sets of interconnected networks or networks
with multiple types of connections, here generally called multilayer networks.
Spreading processes such as information propagation among users of an online
social networks, or the diffusion of pathogens among individuals through their
contact network, are fundamental phenomena occurring in these networks.
However, while information diffusion in single networks has received
considerable attention from various disciplines for over a decade, spreading
processes in multilayer networks is still a young research area presenting many
challenging research issues. In this paper we review the main models, results
and applications of multilayer spreading processes and discuss some promising
research directions.Comment: 21 pages, 3 figures, 4 table
Asymmetric Peer Influence in Smartphone Adoption in a Large Mobile Network
Understanding adoption patterns of smartphones is of vital importance to telecommunication managers in today’s highly dynamic mobile markets. In this paper, we leverage the network structure and specific position of each individual in the social network to account for and measure the potential heterogeneous role of peer influence in the adoption of the iPhone 3G. We introduce the idea of coreperiphery as a meso-level organizational principle to study the social network, which complements the use of centrality measures derived from either global network properties (macro-level) or from each individual\u27s local social neighbourhood (micro-level). Using millions of call detailed records from a mobile network operator in one country for a period of eleven months, we identify overlapping social communities as well as core and periphery individuals in the network. Our empirical analysis shows that core users exert more influence on periphery users than vice versa. Our findings provide important insights to help identify influential members in the social network, which is potentially useful to design optimal targeting strategies to improve current network-based marketing practices
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A Multiplex Social Contagion Dynamics Model to Shape and Discriminate D2D Content Dissemination
Epidemic Spreading with External Agents
We study epidemic spreading processes in large networks, when the spread is
assisted by a small number of external agents: infection sources with bounded
spreading power, but whose movement is unrestricted vis-\`a-vis the underlying
network topology. For networks which are `spatially constrained', we show that
the spread of infection can be significantly speeded up even by a few such
external agents infecting randomly. Moreover, for general networks, we derive
upper-bounds on the order of the spreading time achieved by certain simple
(random/greedy) external-spreading policies. Conversely, for certain common
classes of networks such as line graphs, grids and random geometric graphs, we
also derive lower bounds on the order of the spreading time over all
(potentially network-state aware and adversarial) external-spreading policies;
these adversarial lower bounds match (up to logarithmic factors) the spreading
time achieved by an external agent with a random spreading policy. This
demonstrates that random, state-oblivious infection-spreading by an external
agent is in fact order-wise optimal for spreading in such spatially constrained
networks
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