Paper Info
Title
Multistage Complex Contagions in Random Multiplex Networks
Abstract
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 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">binary</italic> 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 take place over multiple networks (e.g., Twitter and Facebook) or involve <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiplex</italic> networks where individuals engage in different <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">types</italic> of relationships (e.g., acquaintance, coworker, family, etc.). To this end, this paper studies <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multistage</italic> complex contagions that take place over multilayer or multiplex networks. Under a linear threshold based contagion model, we first give analytic results for the expected size of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">global</italic> cascades, that is, cases where a randomly chosen node can initiate a propagation that eventually reaches a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">positive</italic> fraction of the whole population. Next, we analytically derive the probability of triggering global cascades. Then, analytic results are confirmed and supported by an extensive numerical study. In addition, we demonstrate how the dynamics of complex contagions is affected by the extra weight exerted by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hyperactive</italic> nodes and by the structural properties of the networks. In particular, we reveal an interesting connection between the assortativity of a network and the impact of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hyperactive</italic> nodes on the cascade size.
Year
DOI
Venue
2020
10.1109/TCNS.2019.2923388
IEEE Transactions on Control of Network Systems
Keywords
DocType
Volume
Multiplexing,Facebook,Analytical models,Color,Control systems,Twitter
Journal
7
Issue
ISSN
Citations 
1
2325-5870
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Yong Zhuang125413.88
Osman Yagan243043.65