A Comparative Study of GNNs and Rule-Based Methods for Synthetic Social Network Generation

A Comparative Study of GNNs and Rule-Based Methods for Synthetic Social Network Generation

Social network data, and web-graph data in general, sees great amounts of research and is widely used commercially. Due to privacy or other concerns it often cannot be shared verbatim. Synthetic counterparts to such data allow easier and safer sharing. Models currently applied to producing such synt...

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Bibliographic Details
Main Authors: Alex O. Davies, Nirav S. Ajmeri, Telmo De Menezes E. Silva Filho
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Graph neural network
deep learning
social networks
synthetic data
generative model
Online Access:https://ieeexplore.ieee.org/document/10879487/

Internet

https://ieeexplore.ieee.org/document/10879487/

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