SherylHYX/MSGNN
Official code for the LoG2022 paper -- MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian.
This project offers a specialized graph neural network for analyzing signed and directed networks, which are common in social science, biology, and finance. It takes in structured data representing relationships with positive or negative sentiment/interaction and outputs classifications or predictions based on these complex connections. Researchers and data scientists working with networks like trust/distrust relationships, protein interactions, or financial influence would find this useful.
No commits in the last 6 months.
Use this if you need to analyze complex networks where relationships between entities are not just present or absent, but also have a positive/negative direction or sentiment.
Not ideal if your data represents simple, unsigned, or undirected networks, or if you are looking for a general-purpose machine learning model not specifically designed for graphs.
Stars
13
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3
Language
Python
License
MIT
Category
Last pushed
Feb 08, 2025
Commits (30d)
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