Type-to-Token Visualizer

More than Excel

This tool visualizes the changes of moving average type-to-token ratio (MATTR) over the length of a text. While researchers are usually interested in getting a single MATTR value for a text, this tool can show each individual value throughout a text. You may have used spreadsheets like Excel or Google Sheets to visualize your data, but each has limitations. This tool (unlike Excel) is not limited to one million rows, and it will also allow you to interact with the graph by zooming, hovering, and more.

Visualize MATTR

  1. Open your book in WordCruncher. If it is not already in WordCruncher, first add your text with the Indexer.
  2. Run the Phrase Compare report.
  3. Click on the Save results dropdown menu at the bottom.
  4. Select Type-to-Token Ratio files and select one of the following options.
    • Segments: Separated by every word.
    • Levels: Separated by the levels given in the table of contents (e.g., year, month, and day).
  5. Name the file and select either a CSV or TXT file. Either will work, but TXT files are smaller and may be available more quickly.
  6. Click Save.
  7. If you select the levels report, you'll get a message that says, "Only the summary report?"
    • For this visualization tool to work, select no to save the complete report.
  8. Add your file to the TTR Visualizer tool.

Interpreting the Graph

Light blue dotted line: the average MATTR throughout the whole text.

Red and green dotted lines: statistically significant thresholds. Green marks a high MATTR, while red marks a low MATTR. The darker the color, the greater the significance (Z-Score = 1.96 for 95% confidence, 2.576 for 98% confidence, and 3.291 for 99% confidence).


If you do not see a visualization below after adding a file, it is either because you are using an antiquated browser (Internet Explorer), or there is a problem that we have not tested yet. Contact us as soon as possible at and attach the file you are trying to visualize.

TTR Visualizer

Drag and drop your TTR file below to discover new insights worth sharing.

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