TeleHunt is a modular framework that applies reference-driven snowballing with message-level classification and market labeling to discover Telegram cybercriminal communities, delivering the first systematic strategy comparison and a 172-million-message labeled dataset from 6,022 groups.
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Full-field heap morphology comparison via average profiles and pixel-wise intensity provides a more reliable DEM calibration framework than traditional angle-of-repose tuning for granular powders.
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TeleHunt: A Framework and Tool for Efficient Cybercriminal Community Discovery on Telegram
TeleHunt is a modular framework that applies reference-driven snowballing with message-level classification and market labeling to discover Telegram cybercriminal communities, delivering the first systematic strategy comparison and a 172-million-message labeled dataset from 6,022 groups.
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From Angle of Repose to Heap Morphology: Full-Field Calibration of DEM for Granular Powders
Full-field heap morphology comparison via average profiles and pixel-wise intensity provides a more reliable DEM calibration framework than traditional angle-of-repose tuning for granular powders.