Analytical Framework — Rhetorical Analysis
Analytical Frameworks

Analytical Framework — Rhetorical Analysis

Skip to main content
Table of Contents
< All Topics
Print

Analytical Framework — Rhetorical Analysis

Purpose

Apply structured rhetorical analysis to speech corpus to identify:

  1. Authoritarianism markers (in coordination with patriot-speech-analyzer skill)
  2. Enemy construction and out-group framing
  3. In-group identification and loyalty appeals
  4. Crisis-and-rescue narrative structures
  5. Anti-pluralist framing
  6. Charismatic-leader framing
  7. Truth-claim and factuality patterns
  8. Repetition, slogans, and key-phrase tracking

This framework is intended for use across both Trump’s primary corpus and comparative subjects (other speakers, historical baselines).

Authoritarianism Marker Taxonomy (Full)

This taxonomy aligns with the patriot-speech-analyzer skill and democratic-erosion academic literature (Levitsky-Ziblatt, V-Dem, Stanley, Albright):

A. Anti-pluralism

  • A1. Denial of legitimacy of political opposition
  • A2. Casting opponents as criminals, traitors, foreign agents
  • A3. Casting elections as corrupt or rigged before/after results
  • A4. Calls for prosecution of political opponents

B. Norm violation and erosion

  • B1. Threats to ignore court orders or legal constraints
  • B2. Denigration of judges by name
  • B3. Threats against media organizations or specific journalists
  • B4. Denigration of inspectors general, prosecutors, or oversight officials by name
  • B5. Casting career civil servants as adversaries (“deep state”)

C. Enemy construction

  • C1. Demonization of immigrants or specific national-origin groups
  • C2. Demonization of religious groups
  • C3. Demonization of racial or ethnic groups
  • C4. Demonization of intellectuals, universities, or expertise generally
  • C5. Demonization of cultural or political minorities

D. Charismatic-leader framing

  • D1. Self-identification as the only solution / the only one who can fix it
  • D2. Identification of personal grievances with national grievances
  • D3. Personalization of policy (“my generals”, “my justices”)
  • D4. Cult-of-personality cues (event format, audience response patterns)

E. Crisis framing

  • E1. Existential-threat language (“destroying our country”)
  • E2. Apocalyptic framing
  • E3. Manufactured emergencies (declared crises without evidence)
  • E4. War metaphors applied to domestic political situations

F. Calls to action and violence

  • F1. Implicit incitement (ambiguous statements that could license violence)
  • F2. Explicit incitement
  • F3. Justification of violent acts (J6, etc.)
  • F4. Threats against specific individuals

G. Truth degradation

  • G1. Repeated factually-false claims
  • G2. Conspiracy theories (specific verifiable false claims)
  • G3. Attacks on the concept of objective truth (“fake news”)
  • G4. Denial of well-established facts

H. Loyalty mechanisms

  • H1. Explicit loyalty tests for officials
  • H2. Threats against officials who break with leader
  • H3. Praise for officials who demonstrate loyalty
  • H4. Loyalty-by-proximity (proximity to leader = legitimacy)

I. Constitutional / institutional defiance

  • I1. Threats against the Constitution itself
  • I2. Threats against specific constitutional provisions (impeachment, 14th Amendment Section 3, etc.)
  • I3. Calls to suspend or ignore parts of the Constitution
  • I4. Praise for foreign authoritarian leaders’ methods

Coding Procedure

For each speech segment:

  1. Read in full before coding
  2. Identify candidate markers by reference to the taxonomy
  3. Score each marker:
  • Severity: 1 (mild) to 5 (severe)
  • Confidence: 0.0 to 1.0
  • Evidence: Direct quote(s) from the segment
  1. Document context: Audience, event type, date, what came before/after
  2. Cross-coder verification: For published analysis, require at least 2 independent coders with inter-rater reliability check (Cohen’s kappa or similar)

Output Schema

For each speech, produce a structured analysis:


{
  "speech_id": "...",
  "speaker": "Donald J. Trump",
  "date": "2025-XX-XX",
  "event": "...",
  "markers": [
    {
      "code": "A1",
      "label": "Denial of legitimacy of political opposition",
      "severity": 4,
      "confidence": 0.9,
      "evidence": "[direct quote]",
      "context": "[surrounding context]"
    }
  ],
  "summary": "[brief summary of marker pattern]",
  "comparative_baseline_notes": "[optional: comparison to baseline]"
}

Repetition and Slogan Tracking

Beyond the marker taxonomy, track:

  • Recurring slogans (“Make America Great Again”, “Drain the Swamp”, “Witch Hunt”, “Fake News”, etc.) with frequency over time
  • Recurring epithets (“Sleepy Joe”, “Crooked Hillary”, “Pocahontas”, etc.)
  • Recurring conspiracy claims (specific false claims that repeat)
  • Recurring metaphors (war metaphors, infestation metaphors, etc.)
  • Phrase escalation patterns (how the rhetoric around a topic escalates over time)

Maintain a phrase-frequency table that allows queries like:

  • “How many times has Trump used [phrase X] in 2025?”
  • “When did [phrase Y] first appear?”
  • “Which audiences receive [phrase Z]?”

Comparative Baselines

For all rhetorical-analysis work, maintain comparative baselines:

  • Within-subject baseline: Trump 2015 vs 2025 — same speaker, different time
  • Cohort baseline: Trump vs. Biden / Bush / Obama — same office, different speakers
  • Movement baseline: Trump vs. other 2024 GOP primary candidates
  • International baseline: Trump vs. Orbán / Erdoğan / Bolsonaro / Modi (other illiberal-leaning leaders)
  • Historical baseline: Trump vs. Wallace / Long / Coughlin / 1930s authoritarian rhetoric

Comparative analysis avoids the trap of treating Trump rhetoric as uniquely characterizable; the field of comparison provides perspective.

Limitations

  • Coding subjectivity: Marker identification involves judgment; different coders may differ on borderline cases
  • Decontextualization risk: Single quotes may sound more or less severe in isolation; preserve context
  • Audience variation: Same rhetoric may be more or less typical for the audience; account for audience norms
  • Not a clinical or causal claim: Rhetorical analysis describes patterns; it does not diagnose intent or predict behavior

See Also

Was this article helpful?
0 out of 5 stars
5 Stars 0%
4 Stars 0%
3 Stars 0%
2 Stars 0%
1 Stars 0%
5
Please Share Your Feedback
How Can We Improve This Article?