Finding Seeds and Relevant Tags Jointly: For Targeted Influence Maximization in Social Networks

Summary: Jointly selects top-k seeds and top-r tags to maximize influence in a target user set, modeling content-dependent diffusion (e.g., hashtags). To cope with intractability, it delivers heuristics with indexing and optimization for scalable performance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5592
Venue: SIGMOD
Year: 2018
Pagerank: 4.4774498e-05
Overall Rank: 8,626 | 40.05%
DOI: 10.1145/3183713.3199670

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,159	The Solution Distribution of Influence Maximization: A High-level Experimental Study on Three Algorithmic Approaches	2020	SIGMOD	5.1751218e-05
11,075	A Benchmark Study of Deep-RL Methods for Maximum Coverage Problems over Graphs	2024	VLDB	4.1905499e-05
11,142	Host Profit Maximization: Leveraging Performance Incentives and User Flexibility	2024	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
90	A Data-Based Approach to Social Influence Maximization	2012	VLDB	0.00052018478
180	Influence Maximization: Near-Optimal Time Complexity Meets Practical Efficiency	2014	SIGMOD	0.00037101192
338	Influence Maximization in Near-Linear Time: A Martingale Approach	2015	SIGMOD	0.00026987013
1,159	k-Nearest Neighbors in Uncertain Graphs	2010	VLDB	0.00013584223
1,857	Real-time Targeted Influence Maximization for Online Advertisements	2015	VLDB	0.00010318371
2,490	Online Topic-Aware Influence Maximization	2015	VLDB	8.6500989e-05
5,355	Discovering Your Selling Points: Personalized Social Influential Tags Exploration	2017	SIGMOD	5.5518336e-05

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