CELF++: optimizing the greedy algorithm for influence maximization in social networks
Proceedings of the 20th international conference companion on World wide web
Limiting the spread of misinformation in social networks
Proceedings of the 20th international conference on World wide web
Sparsification of influence networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Active learning of model parameters for influence maximization
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
A data-based approach to social influence maximization
Proceedings of the VLDB Endowment
Detecting anti-majority opinionists using value-weighted mixture voter model
DS'11 Proceedings of the 14th international conference on Discovery science
Maximizing product adoption in social networks
Proceedings of the fifth ACM international conference on Web search and data mining
SBP'12 Proceedings of the 5th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Optimal incentive timing strategies for product marketing on social networks
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
Finding influential products on social domination game
Proceedings of the 21st ACM international conference on Information and knowledge management
Influence spread in large-scale social networks --- a belief propagation approach
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
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
Proceedings of the sixth ACM international conference on Web search and data mining
CINEMA: conformity-aware greedy algorithm for influence maximization in online social networks
Proceedings of the 16th International Conference on Extending Database Technology
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
Meme ranking to maximize posts virality in microblogging platforms
Journal of Intelligent Information Systems
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
Maximizing acceptance probability for active friending in online social networks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
The bang for the buck: fair competitive viral marketing from the host perspective
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting changes in content and posting time distributions in social media
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Hierarchical influence maximization for advertising in multi-agent markets
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Analysis of misinformation containment in online social networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
StaticGreedy: solving the scalability-accuracy dilemma in influence maximization
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Personalized influence maximization on social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
How to influence people with partial incentives
Proceedings of the 23rd international conference on World wide web
Weighted graph-based methods for identifying the most influential actors in trust social networks
International Journal of Networking and Virtual Organisations
| Hi-index | 0.00 |
Influence maximization is the problem of finding a small set of most influential nodes in a social network so that their aggregated influence in the network is maximized. In this paper, we study influence maximization in the linear threshold model, one of the important models formalizing the behavior of influence propagation in social networks. We first show that computing exact influence in general networks in the linear threshold model is #P-hard, which closes an open problem left in the seminal work on influence maximization by Kempe, Kleinberg, and Tardos, 2003. As a contrast, we show that computing influence in directed a cyclic graphs (DAGs) can be done in time linear to the size of the graphs. Based on the fast computation in DAGs, we propose the first scalable influence maximization algorithm tailored for the linear threshold model. We conduct extensive simulations to show that our algorithm is scalable to networks with millions of nodes and edges, is orders of magnitude faster than the greedy approximation algorithm proposed by Kempe et al. and its optimized versions, and performs consistently among the best algorithms while other heuristic algorithms not design specifically for the linear threshold model have unstable performances on different real-world networks.