Competitive exclusion in gonorrhea models and other sexually transmitted diseases
SIAM Journal on Applied Mathematics
Competitive exclusion and coexistence of multiple strains in an SIS STD model
SIAM Journal on Applied Mathematics
The Mathematics of Infectious Diseases
SIAM Review
Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Mining knowledge-sharing sites for viral marketing
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
On the bursty evolution of blogspace
WWW '03 Proceedings of the 12th international conference on World Wide Web
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
The dynamics of viral marketing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Epidemic thresholds in real networks
ACM Transactions on Information and System Security (TISSEC)
Word of Mouth: Rumor Dissemination in Social Networks
SIROCCO '08 Proceedings of the 15th international colloquium on Structural Information and Communication Complexity
A Primer of Ecology with R
Competitive influence maximization in social networks
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Finding effectors in social networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Virus propagation on time-varying networks: theory and immunization algorithms
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
A Generalized Linear Threshold Model for Multiple Cascades
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
On the Vulnerability of Large Graphs
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Winner takes all: competing viruses or ideas on fair-play networks
Proceedings of the 21st international conference on World Wide Web
Rumors in a Network: Who's the Culprit?
IEEE Transactions on Information Theory
Understanding and managing cascades on large graphs
Proceedings of the VLDB Endowment
Generalized epidemic mean-field model for spreading processes over multilayer complex networks
IEEE/ACM Transactions on Networking (TON)
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Suppose we have two competing ideas/products/viruses, that propagate over a social or other network. Suppose that they are strong/virulent enough, so that each, if left alone, could lead to an epidemic. What will happen when both operate on the network? Earlier models assume that there is perfect competition: if a user buys product 'A' (or gets infected with virus 'X'), she will never buy product 'B' (or virus 'Y'). This is not always true: for example, a user could install and use both Firefox and Google Chrome as browsers. Similarly, one type of flu may give partial immunity against some other similar disease. In the case of full competition, it is known that 'winner takes all,' that is the weaker virus/product will become extinct. In the case of no competition, both viruses survive, ignoring each other. What happens in-between these two extremes? We show that there is a phase transition: if the competition is harsher than a critical level, then 'winner takes all;' otherwise, the weaker virus survives. These are the contributions of this paper (a) the problem definition, which is novel even in epidemiology literature (b) the phase-transition result and (c) experiments on real data, illustrating the suitability of our results.