The following output was produced by TextLadder using the regular
defaults (maximum # words per text = 25, minimum # encounters = 5,
etc.). The first set of output is the result of TextLadder 2.0's
analysis of Voice of America simplified news texts. Note that this is
a different analysis than the one described in the article. The second
set of output is the result of an analysis of economics news texts.
For short texts (300 - 1000 words):
Sequence List
Pre-Reading List
Included Low-Frequence Words
For longer texts (1000 - 1700 words):
Sequence List
Pre-Reading List
Included Low-Frequence Words
This next piece of output is the list of high-frequency non-list words
obtainable by selecting the "Use TextLadder to generate a list of high-
frequency non-list words" option in TextLadder. In this case, the option
was selected while processing a large number of economics texts. As
the Nation1000, Nation2000, and AWL lists were all chosen, the list
of high-frequency non-list words below represents all the high-
frequency words found in these texts that are not in these 3 lists.
High-Frequency Non-List Words (Economics)
As you can see, both frequency and range information is given about
each word. You can use this information to compile your own "rough
and ready" domain-specific word list. Below is an economics domain-
specific word list that I have compiled on the basis of the list of
high-frequency non-list words above:
Economics Domain Specific List
(Note: When you are building your own lists for use with TextLadder,
it is important that all headwords be on the left margin - i.e. with no
spaces between them and the margin - and that the non-headwords
have either a space or a tab separating them from the left margin.)
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