The network inhibition problem
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
The Mathematics of Infectious Diseases
SIAM Review
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
Epidemic profiles and defense of scale-free networks
Proceedings of the 2003 ACM workshop on Rapid malcode
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
Subgraph sparsification and nearly optimal ultrasparsifiers
Proceedings of the forty-second ACM symposium on Theory of computing
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
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
Viral Marketing for Multiple Products
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
Epidemic spread in mobile Ad Hoc networks: determining the tipping point
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
Suggesting ghost edges for a smaller world
Proceedings of the 20th ACM international conference on Information and knowledge management
Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Recommendations to boost content spread in social networks
Proceedings of the 21st international conference on World Wide Web
Deterministic network interdiction
Mathematical and Computer Modelling: An International Journal
A direct mining approach to efficient constrained graph pattern discovery
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Cascading outbreak prediction in networks: a data-driven approach
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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Controlling the dissemination of an entity (e.g., meme, virus, etc) on a large graph is an interesting problem in many disciplines. Examples include epidemiology, computer security, marketing, etc. So far, previous studies have mostly focused on removing or inoculating nodes to achieve the desired outcome. We shift the problem to the level of edges and ask: which edges should we add or delete in order to speed-up or contain a dissemination? First, we propose effective and scalable algorithms to solve these dissemination problems. Second, we conduct a theoretical study of the two problems and our methods, including the hardness of the problem, the accuracy and complexity of our methods, and the equivalence between the different strategies and problems. Third and lastly, we conduct experiments on real topologies of varying sizes to demonstrate the effectiveness and scalability of our approaches.