Process of emotional analysis on text


I try to resolve use case which catch semantic emotional word on text.
I explan, I have a system of ticketing and I want to analyse the text of requester and the answer of technician for detecting a potential negative or positive sentiments.

But I don’t know where to start because with the type of analysis I have no key word weigth or I don’t know where find the data.

Can you help me ?

And i’m sorry for my bad english.

Thank in advance,

Hello arttom,

this workflow shows how to do sentiment analysis in KNIME.
In order to use it for your use-case, you will have to provide the texts along with a class (positive/negative sentiment) as training data.



Thank’s for your answer,

I have seen the workflow but my document contains no positive or negative values.
I don’t understand how to classify my data on positive or negative sentiment.


Some of these datasets might be useful to you (depending on the language):

First you load the reference dataset into KNIME. Also, you process your original text with a Bag Of Words node and a Term To String node. Then you join your text with the sentiment data, giving each word in your text a sentiment if available in the reference dataset. Finally you aggregate the sentiments with a Group By node (e.g. mean), so that you get a total sentiment of your document.


Ok thank,

I going to test this process,
If I understand, In the first time my analyses is compare bag of word with the dictionary in your links.
And Second create process for explore and create curve etc. (

@arttom I updated my description: You just have one process: After you aggregated the sentiments for the document you are done. You have the sentiment (e.g. a number between -1 and +1) for the document. You don’t need any classification anymore.

Ok thank,

I test this solution

How to use sentiwordnet in knime