TY - CHAP
T1 - Early Detection of Pathogenic Social Media Accounts
AU - Alvari, Hamidreza
AU - Shaabani, Elham
AU - Shakarian, Paulo
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - This chapter introduces a time-decay causality metric and incorporates it into a causal community detection-based algorithm to identify PSMs within a short time frame around their activity. The proposed algorithm is applied to groups of accounts sharing similar causality features and is followed by a classification algorithm to classify accounts as PSM or not. Unlike existing techniques that take significant time to collect information such as network, cascade path, or content, our scheme relies solely on action log of users. Results on the ISIS-B dataset described previously, demonstrate effectiveness and efficiency of our approach. We achieved precision of 0.84 for detecting PSMs only based on their first 10 days of activity; the misclassified accounts were then detected 10 days later.
AB - This chapter introduces a time-decay causality metric and incorporates it into a causal community detection-based algorithm to identify PSMs within a short time frame around their activity. The proposed algorithm is applied to groups of accounts sharing similar causality features and is followed by a classification algorithm to classify accounts as PSM or not. Unlike existing techniques that take significant time to collect information such as network, cascade path, or content, our scheme relies solely on action log of users. Results on the ISIS-B dataset described previously, demonstrate effectiveness and efficiency of our approach. We achieved precision of 0.84 for detecting PSMs only based on their first 10 days of activity; the misclassified accounts were then detected 10 days later.
UR - http://www.scopus.com/inward/record.url?scp=85101159028&partnerID=8YFLogxK
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U2 - 10.1007/978-3-030-61431-7_4
DO - 10.1007/978-3-030-61431-7_4
M3 - Chapter
AN - SCOPUS:85101159028
T3 - SpringerBriefs in Computer Science
SP - 39
EP - 49
BT - SpringerBriefs in Computer Science
PB - Springer
ER -