Hello, I need help with a question, please. Here is the scenario:
I will be performing a Text Mining on content extracted from Facebook, and the textual data was imported to an Excel file. The thing is: This single Excel file has a column named "Posts" and 5.000 rows filled with posts and comments. Can I import to "Text Import" node the file just the way it is, and I'm ready to move on to Text Parsing?! Or should I have one separated Excel file for EACH one of the 5.000 texts?! If so, how can I automate this generation of 5.000 Excel files containing a single text on each one?!
Thanks in advance.
Hello, really thanks for replying back to me.
Here is the scenario: I have a folder containing only one Excel file (below) full of tweets extracted from Twitter, and I want to use it as input for my Text Mining analysis.
Opening this Excel file, you can check a sample of its data (below), which has a lots of rows containing the textual data to be analyzed (where each row contains a different tweet, and therefore we can consider as having N documents inside a single Excel file).
My question is: When using "Text Import" node, can I inport this single Excel file and expect SAS Text Miner to understand that each row is a different text (document) to be analyzed, or am I supposed to have each one of these documents (rows) saved separately?!
For example: let's suppose inside this Excel file I have 150 rows containing differents tweets, can I inport this single file with its 150 rows or should I have 150 excel files (1 for each row)?
Hope I could express myself better this time!
Thanks in advance!
Nice elaboration of your requirement. It helped.
I think you can try with "File Import Node " from the "Sample" tab
File Import Node -> Text Parsing Node -> Text Filter Node ....etc.
In File Import Node do "Right click.." -> "Edit Variables...." and change the Role of "Tweets" variable to "Text"
That should run your Text Mining flow ,
taking each row from your excel as one individual document. (First row "Tweets" will be the variable name )
Thanks.
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