Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Mining knowledge-sharing sites for viral marketing
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The Size of the Giant Component of a Random Graph with a Given Degree Sequence
Combinatorics, Probability and Computing
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
Cost-effective outbreak detection in networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic and role discovery in social networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A note on maximizing the spread of influence in social networks
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Influential nodes in a diffusion model for social networks
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Finding relation between PageRank and voter model
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
Discovery of super-mediators of information diffusion in social networks
DS'10 Proceedings of the 13th international conference on Discovery science
Learning diffusion probability based on node attributes in social networks
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Detecting anti-majority opinionists using value-weighted mixture voter model
DS'11 Proceedings of the 14th international conference on Discovery science
SBP'12 Proceedings of the 5th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Spread of information in a social network using influential nodes
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Identifying influential agents for advertising in multi-agent markets
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Containment of misinformation spread in online social networks
Proceedings of the 3rd Annual ACM Web Science Conference
Opinion formation by voter model with temporal decay dynamics
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Identifying influential nodes in complex networks with community structure
Knowledge-Based Systems
Which targets to contact first to maximize influence over social network
SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Detecting changes in information diffusion patterns over social networks
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
Security games with contagion: handling asymmetric information
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
The social media genome: modeling individual topic-specific behavior in social media
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
StaticGreedy: solving the scalability-accuracy dilemma in influence maximization
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Active learning for networked data based on non-progressive diffusion model
Proceedings of the 7th ACM international conference on Web search and data mining
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We address the combinatorial optimization problem of finding the most influential nodes on a large-scale social network for two widely-used fundamental stochastic diffusion models. The past study showed that a greedy strategy can give a good approximate solution to the problem. However, a conventional greedy method faces a computational problem. We propose a method of efficiently finding a good approximate solution to the problem under the greedy algorithm on the basis of bond percolation and graph theory, and compare the proposed method with the conventional method in terms of computational complexity in order to theoretically evaluate its effectiveness. The results show that the proposed method is expected to achieve a great reduction in computational cost. We further experimentally demonstrate that the proposed method is much more efficient than the conventional method using large-scale real-world networks including blog networks.