Research Programs

Defensive Motivational Nodes (DMN)

The Hidden Language of Our Emotions

A research program of the Ryan Research Institute that develops a framework for inferring the “how” (defense mechanism) and the “why” (affective motivation) behind human language — from everyday conversation to human–AI interaction.

🔗 Resources & Links

• 📄 Paper — Defensive Motivational Nodes (DMN)
• 🗃️ Corpus and Annotation Manual (v1.2) — Synthetic Quadri‑lingual DMN Corpus
• ✍️ Public Essay — Reading the Mind Behind Words — DMN
• 🎙️ Podcast — DMN: How Language Reveals Hidden Motivations

What DMN Is

DMN labels each utterance with a pair: (Defense Mechanism, Affective Motivation) — capturing both how a person is protecting themselves and why they’re speaking that way.

Example 1 — “I’m not upset; it doesn’t matter.” → (Denial, Sadness)

Example 2 — “Everyone is against me on this project.” → (Projection, Anger)

Why it matters

• Most systems tag surface tone (positive/negative/anger/joy).
• DMN adds the defensive posture shaping that tone — the subtext we humans often hear but machines miss.
• This enables empathetic, context‑aware responses and safer, more transparent affective AI.

The Two Axes at a Glance

Defense mechanisms (10, representative): Denial · Projection · Rationalization · Repression/Suppression · Regression · Displacement · Intellectualization · Reaction Formation · Humor · Sublimation

Affective motivations (8, Plutchik‑inspired): Joy · Trust · Fear · Surprise · Sadness · Disgust · Anger · Anticipation

Node = Defense × Motivation (e.g., Projection × Anger, Denial × Fear).

Some pairs are common and informative; others are rare — that distribution itself is signal.

Key Research Findings

• Quadri-lingual pilot corpus (N=300) across EN/KO/FR/KA, with detailed annotation manual.
• Trained annotators achieved substantial agreement on both axes.
• A DMN-guided LLM generated more empathetic responses compared to baseline.
• Dataset and manual are openly available for replication and extension.

How to read a DMN label

• Defense = “how I cope” (distortion, deflection, reframing, channeling)
• Motivation = “what’s driving me” (approach/avoid, protect/confront, connect/withdraw)
• Putting them together gives a 3‑D view of the message: content ↔ defense ↔ emotion.

Ethical Guardrails

• Autonomy — opt-in, user-first interpretations; never override self-narrative.
• Do No Harm — insights framed as possibilities, not verdicts.
• Non-Stigmatization — defenses are normal coping strategies, not pathologies.
• Cultural Humility — multilingual design; avoid WEIRD bias.
• Beneficence — apply only in contexts with clear user benefit.

Disclaimer: DMN is a descriptive inference framework intended for research and educational purposes. It is not a clinical or diagnostic instrument

Applications

• Supportive chat — reflect hidden emotions safely (“It’s okay if part of you feels hurt.”)
• Conflict de-escalation — detect Projection × Anger and respond constructively.
• Research & UX — map defensive patterns over time; evaluate empathy gains.
• Education/Therapy-adjacent — teach healthier coping language (non-clinical use).

Ongoing Work

• Scaling corpus (>2,000 utterances, more languages).
• Developing automated classifiers with calibrated confidence.
• Pre-registered user studies on empathy, trust, and safety outcomes.

Citation

Kim, R. S. B. (2025). Defensive Motivational Nodes (DMN): Inferring Psychological States from Language via Defense Mechanisms and Affective Motivation. Zenodo. https://zenodo.org/records/16778735