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Social networks have enabled user-specific advertisements and recommendationson their platforms, which puts a significant focus on Influence Maximisation(IM) for target advertising and related tasks. The aim is to identify nodes inthe network which can maximize the spread of information through a diffusioncascade. We propose a community structures-based approach that employs K-Shellalgorithm with community structures to generate a score for the connectionsbetween seed nodes and communities. Further, our approach employs entropywithin communities to ensure the proper spread of information within thecommunities. We validate our approach on four publicly available networks andshow its superiority to four state-of-the-art approaches while still beingrelatively efficient.

CKS: A Community-based K-shell Decomposition Approach using Community Bridge Nodes for Influence Maximization