Abstract
Over the past years, political events and public opinion on the Web have been allegedly manipulated by “Pathogenic Social Media (PSM)” accounts dedicated to spreading disinformation and performing malicious activities. These accounts are often controlled by terrorist supporters, water armies, or fake news writers and hence can pose threats to social media and general public. Understanding and analyzing PSMs could help social media devise sophisticated techniques to stop them from reaching their audience and consequently reduce their threat. In this chapter, probabilistic causal inference and well-known statistical technique Hawkes processes are utilized to distinguish between PSM and non-PSM accounts. Results on real-world ISIS-related datasets from Twitter demonstrate that PSMs behave significantly differently from regular users while disseminating information.
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Notes
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Throughout this book, we may use terms normal, non-PSM, or regular users interchangeably to refer to the accounts that do not intend to do harm to the public and social media.
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Alvari, H., Shaabani, E., Shakarian, P. (2021). Characterizing 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_2
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