In comparison, if the texts are transformed into the third DTF, although the frequency information of some words in the text will not match the original situation, the sequence information of words could be kept. This opens the possibility of using the data in this form for other TDM tasks such as sentiment analysis or named entity recognition that require the sequence information of words. If a corpus is published with the expectation that it can be applied to multiple TDM tasks, it makes more sense to prepare the corpus in this format. And of course, it is important to understand how much this format will affect the outcome of different TDM tasks. Therefore, this paper evaluates the usefulness of the third token-based DTF on authorship attribution as a start. In the next sections, the method and the results of the evaluation are reported.