SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model

By Amit Goyal, Wei Lu, Laks V. S. Lakshmanan. 2011 IEEE 11th International Conference on Data Mining, 2011

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Influence Maximization on Social Graphs: A Survey (2018, methodology): “Goyal et al. [30] propose the S IM P ATH algorithm for IM under the LT model.”
Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks (2016, background): “The absolute superiority of SSA and D-SSA are confirmed through extensive experiments on real network data for IM and another topic-aware viral marketing problem, named TVM. Keywords Influence Maximization; Stop-and-Stare; Sampling”
Vital nodes identification in complex networks (2016, methodology): “Till far, there exists a huge number of extensions of the original greedy algorithm by considering the variants of the spreading dynamics [248], by making use of the structural properties of the target networks [249], by integrating advanced optimization methods developed for related problems [250],”
Influence Maximization in Near-Linear Time: A Martingale Approach (2015, methodology): “For IRIE and SIMPATH , we set their internal parameters as recommended in [24] and [21], respectively.”