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behavioral-science

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A deep exploration of how human psychology shapes fraud behavior and how those patterns become measurable signals in transaction data. This article reveals the behavioral, cognitive, and economic forces behind fraud, explaining how ML models detect deviations, anomalies, and intent hidden within financial transactions.

  • Updated Dec 4, 2025

Deep behavioral and machine learning analysis explaining why mobile users systematically report lower satisfaction with AI systems. Includes SHAP explainability, cognitive load modeling, device-context effects, interaction metadata analysis, and end-to-end reproducible research code and visuals.

  • Updated Dec 7, 2025

A deep exploration of loyalty as a multi-dimensional behavioral system shaped by intent, habit, and sensitivity. This article introduces a geometric framework for modeling customer behavior, predicting churn trajectories, and designing ML systems that understand loyalty as a dynamic state, not a metric.

  • Updated Dec 8, 2025
Shepherd

Shepherd is an end-to-end AI Software Engineering platform that supervises the complete software delivery lifecycle—not just code generation, but planning, execution, testing, regression, governance, deployment, and continuous knowledge growth.|Shepherd 将 AI 的一次性交付,转化为组织的长期软件工程资产。

  • Updated Aug 9, 2026
  • Rust

Neurodiagnostic framework utilizing eye movement patterns, pupil dynamics, blink behavior, fixation tracking, and visual attention metrics to identify cognitive distortions, neurological misalignment, adaptive responses, and information-processing disruptions in real time.

  • Updated May 29, 2026

The Behavioral Economics Simulator models the decisions of agents (consumers/investors) influenced by psychological biases in a dynamic, simplified market environment. It was programmed using Eclipse IDE for Java Developers codespace and uses AI bias modeling.

  • Updated Aug 11, 2025

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