The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Distributed construction of connected dominating set in wireless ad hoc networks
Mobile Networks and Applications - Discrete algorithms and methods for mobile computing and communications
Efficient influence maximization in social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Positive Influence Dominating Set in Online Social Networks
COCOA '09 Proceedings of the 3rd International Conference on Combinatorial Optimization and Applications
Power-Law Distributions in Empirical Data
SIAM Review
On positive influence dominating sets in social networks
Theoretical Computer Science
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Positive Influence Dominating Set (PIDS) has applications in Online Social Networks (OSN) such as Viral Marketing and College Drinking Problem. To many reasons finding Minimum PIDS (MPIDS) is very desirable. Beside, one of the most important features that distinguish the graph of OSN from other networks is Power-Law degree distribution. Unfortunately computing MPIDS in Power-Law graph is a NP-Complete problem. Recently, one greedy algorithm has been proposed in the literature for the PIDS problem with time complexity of O(n^3). In this paper, we propose a new greedy algorithm for PIDS which has outstanding time complexity of O(n^2). Theoretical analysis and simulation results are also presented to verify our approach's efficiency. The simulation results reveal that compared to other algorithm, our algorithm efficiently reduces the PIDS size.