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.