Applying the first and the second DTFs to frequency-based authorship attribution does not present any challenge. Take the most well-known method in authorship attribution Burrows’s Delta ( <hi xmlns="http://www.tei-c.org/ns/1.0" rend="Quote_Char">Burrows, 2022</hi>) as an example: Delta test follows the “bag of words” model for representing documents and only requires the frequency of each word in each text to distinguish between authors. The sequence information of words in texts is not necessary. Therefore, the first and the second DTFs keep all the information needed for the Delta test and the transformation does not affect the test results. As a matter of fact, if one only wants to publish a corpus so that the reported classification results of authorship could be verified, all one must do is to publish the document-term-matrix and the metadata table of the corpus.