Abstract
Social networks have been working as a medium to provide cooperative interactions between people. However, as some of users take malicious actions, the social network potentially contains some risks (e.g., information distortion). In this paper, we propose a robust information diffusion (or propagation) model to detect malicious peers on social network. Especially, we apply statistical sequence analysis to discover a peculiar patterns on recommendation flows. Through two experimentation, we evaluated the performance of risk discovery on social network.
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Jung, J.J., Jo, GS. (2007). Risk Discovery Based on Recommendation Flow Analysis on Social Networks. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_87
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DOI: https://doi.org/10.1007/978-3-540-73325-6_87
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
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