AI Toolkit for Textual Analysis

Analytical/Predictive Models: Analyzing Text Data

What Analytical/Predictive Models do

• These are models designed for specific tasks, such as identify patterns, classify content according to specific criteria, extract key information, and find structures within the data.
• These models interpret rather than creating new narratives.

Common Uses in Textual Research

• Classifying documents (by sentiment, topic, genre, etc.)
• Identifying themes and topics across large collections (Topic Modeling)
• Extracting specific entities (names, dates, locations)
• Finding similar texts or measuring textual difference
• Analyzing linguistic features

How They Work (briefly)

• Often rely on Supervised Learning (using pre-labeled examples) or Unsupervised Learning (finding patterns in unlabeled data).

How Researchers Interact with Analytical/Predictive Models

• Researchers typically provide the text content, define analysis parameters (if applicable), and interpret the model's output (classifications, topics, extracted data).

Generative Models: Creating Text & Assisting Analysis

What Generative Models do

• These models (often Large Language Models or LLMs) are best known for creating new text content (drafts, code, translations, etc.) based on user prompts.
• The sophisticated reasoning capabilities also make them powerful assistants for analyzing and interpreting text.

Common Uses in Textual Research

• Content Creation
  • Drafting assistance (outlines, paragraphs, etc.)
  • Brainstorming research questions or keywords
  • Generating alternative paraphrasing or explanation of concepts
  • Translation
• Analysis Assistance
  • Summarizing lengthy texts
  • Answering specific questions based on provided documents or datasets
  • Identifying themes, sentiment, or potential relationships within text.
  • Explaining complex passages or jargon in simpler terms.
  • Generating code (e.g., Python, R) to help perform specific text analysis tasks.
  • Assisting with data cleaning or reformatting based on instructions.

Researcher Interaction

• Primarily through prompt engineering.
• Often involves an iterative process of refinement.