Discourse Analysis

Discourse analysis uses NLP to analyze text structure, coherence, and organization — examining how sentences connect, how topics develop, and how texts achieve communicative goals, going beyond individual sentences to understand document-level meaning.

What Is Discourse Analysis?

• Definition: AI analysis of text structure and organization.
• Scope: Beyond sentences — paragraphs, sections, entire documents.
• Goal: Understand how texts are structured and how meaning emerges.

Discourse Elements

Coherence: How ideas connect logically.
Cohesion: Linguistic devices linking sentences (pronouns, connectives).
Topic Flow: How topics are introduced, developed, concluded.
Information Structure: Given vs. new information.
Discourse Relations: Cause, contrast, elaboration, temporal sequence.
Rhetorical Structure: Hierarchical organization of text.

Applications: Text generation (ensure coherence), summarization (preserve discourse structure), essay grading (assess organization), machine translation (preserve discourse).

AI Techniques: Discourse parsing (RST, PDTB), coherence modeling, topic modeling, neural discourse models.

Tools: Research systems, discourse parsers, coherence evaluation tools.