: This package includes the C++ code of the CRIEG algorithm  to provide an efficient minimum cost seed selection algorithm with theoretical guarantees for competitive influence maximization. CRIEG utilizes an estimation technique to speed up the influence evaluation by first constructing theoretically grounded sketches under the influence diffusion model based on a competitive reverse influence sampling strategy, and then estimating the influence based on the constructed sketches. Experiments on eight large-scale real-world networks show the high efficiency and effectiveness of CRIEG. README files are included in the package, showing how to use the code.
:  Wenjing Hong, Chao Qian and Ke Tang. Efficient Minimum Cost Seed Selection With Theoretical Guarantees for Competitive Influence Maximization. IEEE Transactions on Cybernetics. DOI: 10.1109/TCYB.2020.2966593
: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Dr. Chao Qian (email@example.com).
: The package was developed with C++.
: This package was developed by Dr. Wenjing Hong (firstname.lastname@example.org). For any problem concerning the code, please feel free to contact Dr. Wenjing Hong.