discourse-analysis

Analyze texts to produce structured discourse profiles using spaCy.

Updated Apr 14, 2026

Search Tags:#frameworks #nlp #linguistics #transitivity #discourse-analysis #cda #stance-engagement

Ready to run

npx skills add https://github.com/disabledbydesign/cyborg-methodologies --skill discourse-analysis

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: discourse-analysis
Source: https://github.com/disabledbydesign/cyborg-methodologies/tree/main/discourse-analysis
Command: npx skills add https://github.com/disabledbydesign/cyborg-methodologies --skill discourse-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a framework-informed workflow to convert diverse texts into structured discourse profiles, capturing ideational, interpersonal, and textual metafunctions to support transparent interpretation and comparison.

Core Features & Use Cases

Structured discourse profiling: Extracts transitivity, modality, stance, engagement, and theme patterns to illuminate how texts construct meaning.
Cross-text comparison: Enables researchers to compare patterns across academic, policy, media, and ethnographic materials to surface similarities and differences.
Contextual integration: Generates outputs suitable for inclusion in research notes and project-context documentation, enabling traceable analytical decisions.

Quick Start

Provide a sample text and receive a structured discourse profile plus a concise analytic summary.

Frequently Asked Questions about discourse-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I extract transitivity and modality patterns from text for discourse analysis?▼

Discourse analysis extracts transitivity and modality patterns by tokenizing and parsing text with spaCy to produce a structured profile. This reveals how texts construct ideational and interpersonal meaning across academic, policy, and media materials.

What is the best way to compare stance and engagement across multiple policy documents?▼

Comparing stance and engagement across policy documents requires a structured discourse profile for each text. Cross-text comparison surfaces similarities and differences in how voices are constructed and presuppositions are framed.

Can I use NLP libraries like spaCy to analyze ethnographic materials for linguistic features?▼

You can analyze ethnographic materials using spaCy and optional NLP libraries to tokenize and parse text. The pipeline extracts lexical and syntactic features to generate a structured discourse profile suitable for research notes.

How do I surface hidden presuppositions in media texts using critical discourse analysis?▼

Surfacing presuppositions in media texts involves applying critical discourse analysis frameworks to extract stance, engagement, and theme patterns. This structured profiling illuminates how texts construct meaning and position voices.

Does discourse profiling work for comparing academic and media materials?▼

Discourse profiling works across academic, policy, media, and ethnographic materials to compare texts. It captures ideational, interpersonal, and textual metafunctions to support transparent interpretation and cross-text comparison.