Hi Team,
Good Day.
I am working on a text mining assignment and have built the document matrix using the tm package.
Now I need to run findAssocs from my dtm with some word say 'like' with a correlation of 0.70 but as far as i have been researching it tells it this function is only viable when we have more than 1 doc however in my case i only have 1. So please suggest if there is an alternate to this issue.
Kindly advice.
Hi,
you could split your data differently. E.g. consider each paragraph/section/sentence etc a "document".
Hi Gard,
As i have done all the data cleaning and have created a corpus and then dtm hence all my data be it in rows or column or sentence is not into one single row.
Please see my code below and suggest:
x
Hi Shivi,
as far as I can see, your code is passing a single vector into the Corpus function, and from there into the DocumentTermMatrix() function. So essentially, you're creating a matrix with 1 row and as many columns as there are terms. Hence, no correlations.
It looks like your code is merging together a bunch of reviews. So one option would be to consider each review (i.e. each row in the .csv file) a single document, instead of merging them. That way you could find associations between terms across multiple reviews.
Yes, this was a solution I also had been looking for. I can treat each respondent as a book perhaps.
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