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Keyword density calculation?

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Anybody has tips on how to do that?

I have a long text field (cca. 1000-2000 characters including spaces).

Beside that another field showing keywords, usually not more than 10-15 keywords. These keywords are typed in through Google API and edited by me manually. These can be keywords (or better say key phrases) are separated by comma. These are the words (phrases) I want to make sure I have them in my long text field in sufficient number of times.

I am looking for a way to calculate the keyword density, that is how often do the keywords (the words in the keyword field) appear in the long text field. I do not need to see individual count, sufficient is to have summary count - number of times any keyword appears in the long text.

The density count will give me a percentage =
number of total keywords(phrases)
/ total words in the long text

I looked at this suggestion here but it seems to me Airtable database would explode if I start generating a tag (which seems to me is essentially a multiple choice option) from every single word in the dictionary. I would end up with 1000’s of tags.

Would this bring Airtable servers down? Shall I try it? :crazy_face:

The word manipulation facility in Airtable would go into the same bucket of things as often previously requested grammar check… and perhaps plagiarizing check (SEO de-duplication) and text summarizer. I know I am stretching this far beyond what Airtable is but having these tools would naturally fit in what Airtable is for many typical users today.

1 Solution

Accepted Solutions

(textfld.length-substitute(textfld,phrase1,’ ').length) /phrase1.length

repeat for each phrase. count the rest.
easier done by script, but can be done by formula also

See Solution in Thread

2 Replies 2

(textfld.length-substitute(textfld,phrase1,’ ').length) /phrase1.length

repeat for each phrase. count the rest.
easier done by script, but can be done by formula also

Thank you. Done.

And I found the solution how to split the string of keywords separated by spaces here (same can be applied to words and phrases separated by commas…