Influence Maximization via Graph Neural Bandits Article Swipe
Yuting Feng
,
V.B.C. Tan
,
Bogdan Cautis
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3637528.3671983
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3637528.3671983
We consider a ubiquitous scenario in the study of Influence Maximization (IM), in which there is limited knowledge about the topology of the diffusion network. We set the IM problem in a multi-round diffusion campaign, aiming to maximize the number of distinct users that are influenced. Leveraging the capability of bandit algorithms to effectively balance the objectives of exploration and exploitation, as well as the expressivity of neural networks, our study explores the application of neural bandit algorithms to the IM problem. We propose the framework IM-GNB (Influence Maximization with Graph Neural Bandits), where we provide an estimate of the users' probabilities of being influenced by influencers (also known as diffusion seeds). This initial estimate forms the basis for constructing both an exploitation graph and an exploration one. Subsequently, IM-GNB handles the exploration-exploitation tradeoff, by selecting seed nodes in real-time using Graph Convolutional Networks (GCN), in which the pre-estimated graphs are employed to refine the influencers' estimated rewards in each contextual setting. Through extensive experiments on two large real-world datasets, we demonstrate the effectiveness of IM-GNB compared with other baseline methods, significantly improving the spread outcome of such diffusion campaigns, when the underlying network is unknown.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3637528.3671983
- https://dl.acm.org/doi/pdf/10.1145/3637528.3671983
- OA Status
- gold
- Cited By
- 2
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401856688
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- OpenAlex ID
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https://openalex.org/W4401856688Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3637528.3671983Digital Object Identifier
- Title
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Influence Maximization via Graph Neural BanditsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-24Full publication date if available
- Authors
-
Yuting Feng, V.B.C. Tan, Bogdan CautisList of authors in order
- Landing page
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https://doi.org/10.1145/3637528.3671983Publisher landing page
- PDF URL
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https://dl.acm.org/doi/pdf/10.1145/3637528.3671983Direct link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://dl.acm.org/doi/pdf/10.1145/3637528.3671983Direct OA link when available
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Computer science, Maximization, Graph, Artificial intelligence, Mathematical optimization, Mathematics, Theoretical computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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