Matrix multiplication via arithmetic progressions
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Size-estimation framework with applications to transitive closure and reachability
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Mining the network value of customers
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Mining knowledge-sharing sites for viral marketing
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Maximizing the spread of influence through a social network
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Cost-effective outbreak detection in networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Tractable models for information diffusion in social networks
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Learning influence probabilities in social networks
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Brief announcement: revisiting the power-law degree distribution for social graph analysis
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Scalable influence maximization for prevalent viral marketing in large-scale social networks
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Community-based greedy algorithm for mining top-K influential nodes in mobile social networks
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Orion: shortest path estimation for large social graphs
WOSN'10 Proceedings of the 3rd conference on Online social networks
Affiliation recommendation using auxiliary networks
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Finding relation between PageRank and voter model
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OOLAM: an opinion oriented link analysis model for influence persona discovery
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An analysis of user influence ranking algorithms on Dark Web forums
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Social Network Analysis and Mining for Business Applications
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CELF++: optimizing the greedy algorithm for influence maximization in social networks
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Finding influential mediators in social networks
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Limiting the spread of misinformation in social networks
Proceedings of the 20th international conference on World wide web
Where the blogs tip: connectors, mavens, salesmen and translators of the blogosphere
Proceedings of the First Workshop on Social Media Analytics
CIM: categorical influence maximization
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Maximizing influence spread in modular social networks by optimal resource allocation
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Sparsification of influence networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic-level social network search
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Info-cluster based regional influence analysis in social networks
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
A new centrality measure for influence maximization in social networks
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
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
Mining research topic-related influence between academia and industry
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Incentive compatible influence maximization in social networks and application to viral marketing
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
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WAIM'11 Proceedings of the 12th international conference on Web-age information management
Scalable Affiliation Recommendation using Auxiliary Networks
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A market-based approach to address the new item problem
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A data-based approach to social influence maximization
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Detecting anti-majority opinionists using value-weighted mixture voter model
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Sharing graphs using differentially private graph models
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Influence maximization through identifying seed nodes from implicit social networks
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Estimate on expectation for influence maximization in social networks
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
In-time estimation for influence maximization in large-scale social networks
Proceedings of the Fifth Workshop on Social Network Systems
Influence maximizing and local influenced community detection based on multiple spread model
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Recommendations to boost content spread in social networks
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Finding influential seed successors in social networks
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Influence propagation and maximization for heterogeneous social networks
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Dynamic selection of activation targets to boost the influence spread in social networks
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Optimal pricing in social networks with incomplete information
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
Controlling infection by blocking nodes and links simultaneously
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On the non-progressive spread of influence through social networks
LATIN'12 Proceedings of the 10th Latin American international conference on Theoretical Informatics
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SBP'12 Proceedings of the 5th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
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Ranking User Influence in Healthcare Social Media
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Identifying influential agents for advertising in multi-agent markets
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Multi-Layer network for influence propagation over microblog
PAISI'12 Proceedings of the 2012 Pacific Asia conference on Intelligence and Security Informatics
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Application of the ant colony optimization algorithm to competitive viral marketing
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Maximizing influence spread in a new propagation model
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A network pruning based approach for subset-specific influential detection
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ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Learning the Strength of the Factors Influencing User Behavior in Online Social Networks
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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
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Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Probabilistic solutions of influence propagation on social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Understanding latent interactions in online social networks
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Probabilistic graph summarization
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A probability based algorithm for influence maximization in social networks
Proceedings of the 5th Asia-Pacific Symposium on Internetware
Pagerank with priors: an influence propagation perspective
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Scalable topic-specific influence analysis on microblogs
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Preference-based mining of top-K influential nodes in social networks
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The Journal of Supercomputing
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Weighted graph-based methods for identifying the most influential actors in trust social networks
International Journal of Networking and Virtual Organisations
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Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread of influence. In this paper, we study the efficient influence maximization from two complementary directions. One is to improve the original greedy algorithm of [5] and its improvement [7] to further reduce its running time, and the second is to propose new degree discount heuristics that improves influence spread. We evaluate our algorithms by experiments on two large academic collaboration graphs obtained from the online archival database arXiv.org. Our experimental results show that (a) our improved greedy algorithm achieves better running time comparing with the improvement of [7] with matching influence spread, (b) our degree discount heuristics achieve much better influence spread than classic degree and centrality-based heuristics, and when tuned for a specific influence cascade model, it achieves almost matching influence thread with the greedy algorithm, and more importantly (c) the degree discount heuristics run only in milliseconds while even the improved greedy algorithms run in hours in our experiment graphs with a few tens of thousands of nodes. Based on our results, we believe that fine-tuned heuristics may provide truly scalable solutions to the influence maximization problem with satisfying influence spread and blazingly fast running time. Therefore, contrary to what implied by the conclusion of [5] that traditional heuristics are outperformed by the greedy approximation algorithm, our results shed new lights on the research of heuristic algorithms.