Terrorist Activities Detection via Social Media Using Machine Learning

Computer Engineering

Social media is to be considered as the richest source of human-generated text input. Internet users' opinions, feedback, and criticisms are a reflection of their attitudes and feelings towards many subjects and concerns. Any group of people would not be able to read such a massive amount of material. Social media has thus developed into a crucial instrument for disseminating their ideas and persuading or luring individuals, in general, to participate in their terrorist actions. The most popular and convenient method for quickly reaching a large number of people is Social media. The construction of a system that can automatically identify tweets that promote terrorism using real-time analytics and the Apache Spark machine learning framework was the main emphasis of this paper. The proposed approach attempts to increase accuracy while being fully dependent on training data. By preventing the terrorist accounts from Social media, the public will be protected from their propaganda and fear-mongering.

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