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Text Analysis Tools

A companion to our Text and Data Mining Sources infoguide, this guide will take you through how to use several text analysis tools

Additional Free Tools

The following web-based tools, software programs, and programming languages are used for text analysis. 

  • AntCont. A free text corpus analysis toolkit for concordancing and text analysis.
  • Concordle. Creates word clouds based on the user's corpus.
  • Lexos. Allows users to upload their corpus, clean the documents, and then perform visualizations or analyze them. Files are limited by size and type.
  • MALLET. Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
  • Python. A programming language that is used by many for text mining and analysis. The Programming Historian has a series of lessons on using Python for manipulating and analyzing text data. 
  • R and RStudio. Open source statistical analysis software that rely on community driven packages to mine data. R is script heavy, meaning a programming background is highly recommended, but it offers the most flexibility with mining as well as creating visualizations of the results. See the book Text Mining with R and The Programming Historian's "Basic Text Processing in R." 
  • Text Analysis Portal for Research (TAPoR). Discover research tools for studying texts including detailed search and curated lists.

Further Reading

See the following journal articles and blog posts to learn more about what text analysis is, the various methods of text analysis, and how text analysis has been used in scholarship.