LogoLogo
  • About
  • Digital Scholarship
    • DS Methods Overview
      • ¶ Data Visualization
        • Basic Charts
        • Timeline
        • Treemap
        • Network
      • ¶ Mapping
        • GIS
        • Story Maps
        • Maps as Interface
      • ¶ 3D & Immersive Technologies
        • Augmented Reality & Virtual Reality
        • 3D Modeling & Laser Scanning
        • Immersive Games
        • 360 Degree Capturing
      • ¶ Digital Exhibits
        • Example Exhibits
      • ¶ Hypertext
        • Publishing & Presenting
        • Multimedia
        • Narratives & Games
      • ¶ Textual Encoding Initiative
        • What Does TEI Markup Look Like?
        • Facsimiles & Critical Editions
      • ¶ Text Analysis
        • Out of the Box vs Coding and Scripting
        • Text Analysis Examples
    • Introduction to Data
      • ¶ What is Data?
        • Structured & Unstructured Data
        • Quantitative & Qualitative Data
        • Humanities & Data
      • ¶ What is Data Visualization?
      • ¶ DS Data Projects
        • Getting Started Questions
        • Project Examples
        • Visualization Tools
      • ¶ Research Data Lifecycle
        • Data Management Best Practices
      • ¶ Glossary
    • Introduction to Mapping
      • ¶ What is Spatial Data?
      • ¶ Vector and Raster Data
        • Vector and Raster Data Examples
        • File Format Examples
      • ¶ Starting a Mapping Project
        • Getting Started Questions
        • Project Examples
        • Mapping Tools and Platforms
    • Introduction to Digital Exhibits
      • ¶ What is a Digital Exhibit?
        • Related Concepts
      • ¶ Starting a Digital Exhibit
      • ¶ Exhibit Examples
      • ¶ Platforms
  • Digital Pedagogy
    • ¶ What is Digital Pedagogy?
    • ¶ Considerations
    • ¶ Recommendations
    • ¶ Assignment Design
      • Learning Outcomes
      • Mode/Method/Tool Process
      • Assignment Examples
    • ¶ Evaluation
      • Assignment Criteria
    • ¶ Maintenance & Archiving
      • Recommended File Formats
  • Accessibility
  • Skills
  • Tools
Powered by GitBook
On this page
Export as PDF
  1. Digital Scholarship
  2. DS Methods Overview

¶ Text Analysis

PreviousFacsimiles & Critical EditionsNextOut of the Box vs Coding and Scripting

Last updated 4 years ago

Text analysis involves using digital tools and one’s own analytical skills to explore texts, be they literary works, historical documents, scientific literature, or tweets. Approaches can be quantitative (e.g., word counting) and qualitative (e.g., and ), and tools can range from coding and scripting languages to "out of the box" platforms like and .

In the humanities, text analysis is closely associated with the concept of , which essentially means using computational methods to explore and query large (sometimes massive) corpora. The corpa or datasets, as they are more commonly called in the sciences and social sciences, can be structured or unstructured, and the results can have a data visualization component.

Related Terms:

  • Text mining (a term used more in the humanities), data mining (a term used more in the sciences and social sciences), and web scraping are techniques that use coding, scripting, and "out of the box" tools to gather text and create a corpus (or dataset).

topic modeling
sentiment analysis
Voyant
Lexos
distant reading