What is the equivalent of tokens in a DTM?

Question

BlackTom AI · Accepted Answer

When approaching the concept, it's helpful to map what is meant by tokens in a Document-Term Matrix (DTM).
Option 1: 'words' — This is correct. In a DTM, rows typically represent documents and columns correspond to tokens that appear in the corpus; these tokens are usually individual words or terms extracted from the text. So, recognizing tokens as words aligns with the standard construction of a DTM.
Option 2: 'objects' — This is not accurate in the context of a DTM. 'Objects' are not a typical unit of analysis or a standard feature representation in a document-term layout; DTMs focus on textual units like words or terms, not arbitrary objects.
Option 3: 'values' — While a DTM does contain values (the counts or frequencies) in the matrix cells, 'values' are not what the tokens themselves are. The tokens are the columns (features); the numbers in the cells are the counts or frequencies of those tokens in each document.
Option 4: 'terms' — This is correct. In many discussions of DTMs, tokens are referred to as terms (synonymous with words) that appear in the documents; the matrix is often called a term-document matrix or a document-term matrix depending on orientation, but 'terms' is a valid and common synonym for the units represented by the columns.

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