Transformer models with user adapters extract behavioral signals from encrypted network traffic that correlate with stress, loneliness, and sleep issues via sparse features and GEE models, outperforming handcrafted features for within-person changes.
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Systematic review of 80 papers shows TTP extraction shifting to transformer and LLM methods but limited by narrow datasets, single-label focus, and low reproducibility.
Social media data functions as passive geospatial sensing for public opinion and behavior via a structured workflow and case studies on topics like COVID-19 vaccines and urban accessibility.
citing papers explorer
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Learning Behavioral Signals from Encrypted Smartphone Network Traffic
Transformer models with user adapters extract behavioral signals from encrypted network traffic that correlate with stress, loneliness, and sleep issues via sparse features and GEE models, outperforming handcrafted features for within-person changes.
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A Guide to Using Social Media as a Geospatial Lens for Studying Public Opinion and Behavior
Social media data functions as passive geospatial sensing for public opinion and behavior via a structured workflow and case studies on topics like COVID-19 vaccines and urban accessibility.