This project, hosted on my public GitHub repository synthetic_network_creation_and_visualization, is inspired by the foundational work presented in "NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks" by Shashank Pandit, Duen Horng Chau, Samuel Wang, and Christos Faloutsos. The code generates an artificial network with customizable node roles, including "Fraud," "Accomplice," and "Honest," allowing for adaptable modeling of different network types. The visualization often corresponds to a "ball of yarn" due to the dense network of edges connecting nodes within the simulated network, emphasizing the relationships between nodes. This open-access repository provides a robust tool for creating and visualizing synthetic networks, supporting further research and network structure analysis. Link to the original paper: https://kilthub.cmu.edu/articles/journal_contribution/NetProbe_A_Fast_and_Scalable_System_for_Fraud_Detection_in_Online_Auction_Networks/6607661/1/files/12098213.pdf
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This project was based off of the publication, "NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks" by Shashank Pandit, Duen Horng Chau, Samuel Wang, Christos Faloutsos. This code allows the generation of an artificial network and then provides a visualization of the network.
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KayleeSloat/synthetic_network_creation_and_visualization
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This project was based off of the publication, "NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks" by Shashank Pandit, Duen Horng Chau, Samuel Wang, Christos Faloutsos. This code allows the generation of an artificial network and then provides a visualization of the network.
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