Abstract
In this chapter, we adopt the causal inference framework described previously along with graph-based metrics to distinguish PSMs from normal users within a short time of their activities. We propose both supervised and semi-supervised approaches without taking the network information and content into account. Results on the ISIS-A dataset demonstrate the advantage of our proposed frameworks. We show our approach achieves 0.28 improvement in F1 score over existing approaches with the precision of 0.90 and F1 score of 0.63.
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Alvari, H., Shaabani, E., Shakarian, P. (2021). Graph-Based Semi-Supervised and Supervised Approaches for Detecting Pathogenic Social Media Accounts. In: Identification of Pathogenic Social Media Accounts. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-030-61431-7_6
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DOI: https://doi.org/10.1007/978-3-030-61431-7_6
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