RapidMiner is a terrific tool for non-programmers to do data mining and text analysis. This is a tutorial on how to do sentiment evaluation with RapidMiner. This tutorial utilizes our free Twinword Sentiment Analysis API.
- RapidMiner Studio (download free trial)
- Twinword Sentiment Evaluation API Essential (get absolutely free API crucial at Mashape)
Step 1) Install Web Mining Extension for RapidMiner
Prior to going any further, you should really already have RapidMiner installed. If not, check out the link above, download and set up the full computer software to start your free of charge trial.
RapidMiner is a good tool already packed with text processing capabilities. In addition, we can use it to connect Elle Decor to third celebration APIs to do much more work, such us connecting to our Twinword Sentiment Analysis API.
Nevertheless, before we can do this, we want to install an extension that will permit us to send information to the internet and capture the response.
1st, start RapidMiner and in the major menu, go to Assistance > Marketplace (Updates and Extensions)…
With the Web Mining extension installed, you can now connect to REST APIs to process your text and data.
Step 2) Setup the Connection to the API
Go to the “Design” web page in RapidMiner.
To connect to our internet API, you will need to have to use the Net Mining extension you just downloaded.
On the left “Operators” pane, find the operator known as “Enrich Data by Webservice” listed under Net Mining > Solutions > Enrich Information by Webservice.
Drag it to the center “Main Course of action” pane and drop it there.
Pick the operator we just dropped in the “Process” pane to edit the “Parameters” on the suitable pane.
We want to set the following parameters:
|regular expression queries||
Note: we are working with Normal Expression queries to match and grab the four things (“type”, “score”, “ratio”, and “keywords”) we want out of the complete JSON response that we would get back from the API.
Right after your accomplished, it should look something like this:
Step 3) Setup the Input Text
Now that we have the ideal settings to connect with the API, we require text to Elle Decor send.
Just before we can start, make confident that you have the “Text Processing” extension installed. If not, go back to the Marketplace (Updates and Extensions) to install it, the exact same way you installed the “Web Mining” Elle Decor extensions.
First, lets metal platform bed develop a sample document with sample text. Again, in the left “Operators” pane, uncover the “Create Document” operator beneath Text Processing > Develop Document.
Drag it to the center “Process” pane and drop it there. Choose it so that we can edit the “Parameters” in the correct pane.
Then click on “Edit Elle Decor Text…” in the “Parameters” pane to paste in some sample text. For objective of this tutorial, we will just sort one thing like the following:
I love hotdogs. Hotdogs are the greatest. They are hot and scrumptious.
Now we have a document. Great! Even so, the operator (“Enrich Data by Webservice”) we set up to connect to the API expects an input type named “Example Set”, not a “Document”.
So, we have to have to convert the “Document” type text we just produced into an “Example Set”. Luckily, there is a further operator ideal next door named the “Documents to Information” operator. You can obtain the operator beneath Text Processing > Documents to Data.
Drag and drop it into our “Process” pane and pick it.
In the “Parameters” Elle Decor pane, just type
text in the “text attribute” field.
Step 4) Link the Operators Up
You’re almost there! Just connect the operators.
- Build Document out connects to
- doc of Documents to Data and its exa connects to
- Exa of Enrich Information by Webservice and its Exa connects to
Soon after you’re completed, it ought to appear one thing like this:
Step five) Run It!
All that’s left now is to click run (the blue play icon at the best).
After operating it, you must see the parisian metal platform “Results” web page with our 1 row with a number of columns such as our “text” about hotdogs and the the four items (“score”, “keywords”, “type”, “ratio”) we utilized Standard Expression to grab out of the JSON response from the Sentiment Evaluation API.Note: If you want a lot more explanation on the which means of the score and ratio, please read our blog post about Interpreting the Score and Ratio of Sentiment Evaluation.
If a thing goes wrong, you can go back to the “Design” web page and make the vital modifications and run it once more.
Here is a link to Twinword’s Free of charge Sentiment Evaluation API talked about in this report.
Very good luck. If you have any queries or difficulties, please really feel no cost to make contact with us at email@example.com.