Scholars@Duke publication: GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs

GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs

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Published version (DOI)

Duke Scholars

Contributor Neil Gong Electrical and Computer Engineering

DOI

10.1109/ICDM.2017.56

Citation

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Chicago

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GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs. (n.d.). https://doi.org/10.1109/ICDM.2017.56

“GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs,” n.d. https://doi.org/10.1109/ICDM.2017.56.

GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs. In.

GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs. Manual, doi:10.1109/ICDM.2017.56.

GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs.

DOI

10.1109/ICDM.2017.56