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Social Persona Profiling

Profile people from social-media traces — avatar, profile/cover background, nickname, privacy/visibility settings, chat behavior, shared content, self-reported labels — across platforms (WeChat, WhatsApp, Instagram, LinkedIn, Telegram, X) and cultures. Delivers an evidence-weighted persona read, relationship analysis, or exploratory next-step guidance. Built on Big Five (OCEAN), self-presentation (Goffman/Snyder), self-discrepancy (Higgins), defense mechanisms (Vaillant), attachment and burnout signals. Three-tier confidence grading, moderator adjustment for age/culture/baseline, projection-symmetry check, Barnum-effect filter. Use when: "analyze this person", "is this person trustworthy", "relationship crisis analysis", "what should I do next".

personAuthor: user_7fbe8d41hubcommunity

social-persona-profiling

⚠️ Privacy & Use Warning (read first)

This skill produces speculative personality inferences from limited social traces — it is NOT a psychological assessment, NOT a mental-health diagnosis, and NOT suitable for consequential decisions.

  • Sensitive personal data: Inputs (avatars, chat logs, shared content) are personal data. Obtain the subject's consent where feasible; do not profile public figures, minors, or people without reasonable access to their traces.
  • False positives are common: Personality inferences from social traces have low validity. Every output is a working hypothesis, not a fact. Cross-check with direct interaction before acting.
  • Not for consequential decisions: Do NOT use outputs for hiring, credit, legal, medical, or relationship-ending decisions. The skill provides exploratory discussion points, not directive guidance.
  • Mental-health boundary: Frameworks referencing depression/anxiety/emotional-distress (e.g. self-discrepancy) are theoretical patterns, NOT diagnoses. If the subject shows distress signs, recommend professional help — do not label or diagnose.
  • Non-directive: "What should I do next" outputs are exploratory discussion points for the user's own judgment, not instructions to execute.

A methodology for persona profiling and relationship analysis from social-media traces, aiming to be professional yet actionable — use scientific frameworks like the Big Five for grounded inference, use moderators to avoid misreading, and use three-tier confidence grading to stay honest. Guard against two failure modes at once: dressing the client's subjective narrative up as objective conclusion (dishonest), and giving Barnum-style one-size-fits-all readings or culture/age-mismatched labels (unprofessional).

When to use

  • User provides a social avatar / profile / chat history (WeChat, WhatsApp, Instagram, LinkedIn, Telegram, etc.) and asks "what's this person's personality?"
  • User is in a relationship crisis and wants attribution + how to handle it
  • User wants a "persona profile report" or "relationship analysis report"
  • Assessing the credibility of a self-description / chat history
  • Scenario-based read on people: whether to deepen a work collaboration, advance a relationship, trust a friend, or spot manipulation/scams
  • User requests exploratory (non-directive) discussion of possible next steps, with explicit understanding outputs are hypotheses not instructions

Hard Rules (learn these first, then the steps)

  1. Three-tier confidence grading (mandatory) — every conclusion must fit one tier:
    • High (objective fact): what the avatar is, what the background shows, verbatim chat quotes — directly observable, no interpretation.
    • Medium (behavioral inference): tendencies inferred from behavior (e.g. "fast replies + voice messages → high trust") — has behavioral evidence but is one of several explanations.
    • Working hypothesis (theory construction): three-layer needs, core contradictions, stress mechanisms, precise Big Five placement, "true inner self" — products of the analytic framework; to be verified, never a basis for action.
  2. What the client says is not fact. The client is both information source and stakeholder; their account carries confirmation bias, self-serving bias, and emotional coloring. Tag the source of any client statement, and question its reliability.
  3. Projection-symmetry check (mandatory): if the analyst's description of the subject (e.g. "hard shell, soft core") resembles the analyst's own structure, warn explicitly — you cannot distinguish "genuinely read them" from "projected myself". Downgrade all "inner core" conclusions about the subject by one tier.
  4. The subject is not present and cannot defend themselves. All attribution about the subject is single-sided; the report must state this power asymmetry.
  5. Present the final analysis, leave no editing traces. Do critical self-review before producing and fold results into conclusions, but the report body must NOT contain meta-language like "correction:", "clarification", or "my review found". The client wants a clean, deep final judgment, not a self-congratulatory audit trail. Weave methodology caveats (validity ceiling, projection symmetry) into the relevant analysis sections; don't add a separate "audit chapter" to show off.
  6. Must close with a psychological formulation. Don't stop at behavior listing — give an integrated professional formulation: "what kind of person is this". Integrate self-monitoring / self-discrepancy (Higgins) / self-esteem type (contingent & fragile) / defense mechanisms / attachment / burnout, and give a one-sentence formulation. Note frameworks differ in validity (see toolbox): attachment only as a tendency, never a definitive type; Big Five only at "medium" confidence.
  7. Adjust before interpreting. Every signal must be calibrated by moderators (age/developmental stage, cultural baseline, personality baseline, digital-native generation) before interpretation. Behavior within the baseline carries no personality signal; only "deviation from baseline" can be a signal.

Theory Toolbox (quick ref — see @references/psych-frameworks.md)

Ranked by scientific validity. Theories generate hypotheses to verify, not labels to stick.

| Framework | Validity | Use & warning | |---|---|---| | Big Five OCEAN | High (backbone) | The only widely validated personality structure. Social traces → five traits only weakly correlated (r .1–.3); needs long-term multi-context samples; always mark "medium", never "high" | | Self-presentation / self-monitoring (Goffman / Snyder) | Medium-high | An avatar is "the me I want to show", not the real me; first judge whether the subject is a high or low self-monitor to gauge the signal-to-noise ratio of their traces | | Self-discrepancy (Higgins) | Medium-high | Ideal–actual gap → dejection; ought–actual gap → anxiety; large persona–actual gap = emotional-distress risk | | Defense mechanisms (Vaillant) | Medium | Watch the first reaction to setbacks (rationalization / denial / intellectualization / humor); never type someone from a single reaction | | burnout (Maslach) | Medium | Requires exhaustion + cynicism + reduced efficacy together; "tired" alone ≠ burnout | | Attachment type | Low (use with caution) | Needs AAI/ECR scales; inferring from avatar/chat has very low validity; working hypothesis only, must be flagged, never definitive | | MBTI / astrology | Very low | Social currency / self-labels, not empirical tools; self-reports only reflect "how they want to be seen", never count as Big Five evidence |

Moderators (read before interpreting — see @references/moderators.md)

The same signal can mean opposite things across groups. Interpreting without adjusting is the most common error.

  • Age / developmental stage: teen anime/idol avatars = normal identity exploration (not "immature"); middle-aged child/scenery avatars = normal life-focus shift (not "hiding the self"). Avatar information content decreases with age; over-reading older adults' avatars is the most error-prone.
  • Cultural baseline: collectivist/high-context cultures (East Asia, Latin America, Middle East) — non-real-person avatars, indirect self-display, restricted visibility are cultural norms, not personal signals; individualist/low-context cultures (North America, Western Europe) — direct real-face display is more common. The same behavior is baseline in one context and a signal in another.
  • Personality baseline: introverts using non-real avatars and extroverts using real photos are both baselines, not signals. Read deviation from the personal baseline, not the absolute type.
  • Digital-native generation: Gen Z multi-platform multi-persona is the norm; a single-platform image ≠ the whole person. Older users' single-platform real-identity is the norm.
  • Gender / ethnicity: group-level trends have huge individual variance; beware stereotyping; cross-ethnic comparison is essentially cultural difference — attribute to culture, not ethnicity.

Application Scenarios & Ethics

  • Scenario split: workplace collaboration (reliability & boundaries), romantic decisions (attachment & values), friendship trust (consistency), scam detection (inconsistency & manipulation signals) — different scenarios have different decision criteria and risk appetite; confirm the client's scenario first.
  • Client intent screening: if the profiling aims to manipulate, PUA, deceive, or harm the subject, refuse.
  • Prohibited: never for discriminatory decisions (hiring, credit, insurance, background-check scoring).
  • Subject dignity: profiling is single-sided; the subject is unaware and cannot defend themselves; results must not leak to third parties or be used for public judgment.

Steps

This is a pure LLM analysis task (no deterministic script steps); all steps are [LLM]. Architecture: Workflow / Prompt Chaining (sequential steps + the audit checkpoint at step 6).

  1. [LLM] Inventory & classify data: sort all material into "objective fact / behavior / user-transcribed / self-reported". First confirm what you saw directly (images can be read directly) vs what the user transcribed (transcription loss).
  2. [LLM] Moderator adjustment first: confirm the subject's age/developmental stage, cultural/subcultural baseline, personality baseline, digital-native generation. Remove "baseline-normal" behavior (carries no personality signal); keep only "deviation from baseline" as candidate signals. See @references/moderators.md.
  3. [LLM] Layered persona: public persona / private self / self-reported layer. Keep the three separate; don't rush into a "unified narrative". If the subject has a self-reported persona, further split into "constructed persona / self-perception / actual image" and analyze the gaps — persona and actual often run opposite; the size of the self-perception–actual gap is itself a key insight (large gap = low self-awareness or unwillingness to admit).
  4. [LLM] Grade confidence item by item: three tiers (objective fact / behavioral inference / working hypothesis). Better low than high. Big Five always "medium"; attachment only a working hypothesis.
  5. [LLM] (if a relationship event) Attribution: reconstruct the timeline, but state it is single-sided. Responsibility assignment must declare "contains self-serving bias".
  6. [LLM] Critical review (mandatory): run the bias checklist (below) before producing, and give a "specific over-inference list".
  7. [LLM] Psychological formulation close: integrate the toolbox into "what kind of person is this" + a one-sentence formulation.
  8. [LLM] Action guidance: besides the report, give actionable "what to do next". Confirm the client's scenario (workplace / dating / friendship / scam), organize into "do now / observation period / long-term strategy"; advice rests only on dependable facts, working hypotheses only flag what to watch. Templates: @references/consulting-playbook.md.

Output Format (report skeleton)

Recommended structure, trim as needed:

  1. Data basis: objective facts (no acquisition-method tags unless data was filtered/transcribed).
  2. Layered persona: public / private / self-reported; or persona / self-perception / actual. Analyze inter-layer gaps.
  3. Psychological dynamics: integrate the toolbox, tie each to behavioral evidence.
  4. Psychological formulation: what kind of person + one-sentence formulation (the core deliverable).
  5. Big Five placement: five traits, all "medium" confidence.
  6. Action guidance (what to do next): by scenario, "do now / observation / long-term" three tiers, resting on dependable facts. Templates: @references/consulting-playbook.md.
  7. Methodology note: validity ceiling + position statement, brief, at the end.

Failure Handling

| Scenario | Action | |------|------| | Insufficient data (single avatar / single post) | State only very limited inference is possible, refuse a full formulation; suggest multi-context, longitudinal samples | | Client requests discriminatory / manipulative use | Refuse, state the ethical boundary (see Application Scenarios & Ethics) | | Cannot confirm subject baseline (age / culture unknown) | Ask the client first; if unavailable, declare "baseline not calibrated, overall confidence downgraded one tier" in the report | | Inference conflicts with client expectation | Don't bend to expectation; present the evidence-supported conclusion and flag the divergence | | Material contains identifiable sensitive info | Analyze internally only; don't restate identifiable details in output; remind the client about the subject's privacy |

Bias Checklist (self-check before producing)

  • Validity ceiling: social avatar/traces → personality has only weak academic support (Gosling's physical/virtual environment personality expression, cross-cultural collectivist explanations of avatar choice, broad Big Five correspondence research); supports only weak correlation at "broad trait + cultural background" level, not "type → fixed personality" mapping.
  • Confirmation bias: was the material filtered by the client? Did they only give parts supporting one reading? (only applies if data is filtered/fragmentary; skip if the client states it's a complete conversation flow)
  • Information cascade loss: analysis → user transcription → user memory/emotion; distortion compounds at each layer. (only when relying on secondhand transcription; not when transcription is factual or images are read directly)
  • Narrator-protagonist effect: the client narrates, tending to cast themselves as the "clear-eyed observer" and the subject as the "observed object".
  • Self-serving bias: does attribution happen right after the client's emotional event? Does it assign problems to the subject's "structure" to protect the self?
  • Narrative over-integration: are independent elements (nickname + avatar + background) forced into one "unified theme"? When elements don't cohere, the so-called "tension aesthetic" is often the analyst's framework imposition.
  • Circular reasoning: the persona was inferred from these behaviors, then used to explain them — that is consistency checking, not causal explanation.

Pitfalls

  • Barnum effect (biggest trap): vague descriptions feel accurate to everyone ("strong outside, soft inside", "longing to be understood"). Test: would this hold for any random person? If yes = delete it. Every formulation must be specific, differentiating, falsifiable.
  • Attachment labeling: judging "avoidant/anxious attachment" from avatar/chat has very low validity and needs scales. Working hypothesis only, flagged, never definitive.
  • Clinical-term abuse: "learned helplessness", "regression", "burnout" have specific meanings; don't use casually. Say "expression of helplessness" not "learned helplessness".
  • Treating MBTI/astrology self-report as measurement: ENTJ, earth-sign etc. are self-idealizing labels; they only reflect "how they want to be seen", never Big Five evidence.
  • Reading cultural norm as personality: collectivist-culture users using non-real avatars and restricted visibility (group/time-limited) is common (privacy vigilance + indirect self-display); don't read cultural norm as a personal signal.
  • Romanticizing: a polite reply ("thanks", "I know") ≠ "trust rising" or "we've seen each other's vulnerability".
  • Over-inferring from one sample: a "behavior pattern" induced from a single event has n=1; not a confirmed stable pattern.

Verification

After producing the report, self-check:

  • Was moderator adjustment done first (age/culture/personality baseline/digital-native generation), removing "baseline-normal" signals?
  • Was the use scenario and client intent confirmed compliant (non-manipulative, non-discriminatory)?
  • Does every conclusion carry a confidence tier tag?
  • If data was client-filtered/transcribed, was information loss flagged? (skip when data is complete and transcription factual — avoid inapplicable disclaimer noise)
  • Was the projection-symmetry check done (if applicable)?
  • Is the report body clean — no meta-language like "correction: / clarification / my review found", only final analysis?
  • Does it close with a clear psychological formulation (what kind of person + one sentence), not stop at behavior listing?
  • Is there a "specific over-inference list" that singles out and downgrades the weakest claims?
  • Was the client reminded that the subject cannot defend themselves in this document? If any answer is "no", the report fails the honesty bar — rework.