Titlebook: Identification of Pathogenic Social Media Accounts; From Data to Intelli Hamidreza Alvari,Elham Shaabani,Paulo Shakarian Book 2021 The Auth

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Introduction

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Graph-Based Semi-Supervised and Supervised Approaches for Detecting Pathogenic Social Media Accounto 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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Characterizing Pathogenic Social Media Accounts,ell-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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Feature-Driven Method for Identifying Pathogenic Social Media Accounts,ated website, etc.). Finally, for the content-related information, we examine attributes (e.g., number of hashtags, suspicious hashtags, etc.) from tweets posted by users. Experiments on real-world Twitter data from different countries demonstrate the effectiveness of the proposed approach in identifying PSM users.