How to analyze the tonality of language using IBM Watson Tone Analyzer? – Quickwork Support Center

This article demonstrates the tone identification of a message received using IBM Watson Tone Analyzer.

What you'll need:

Skill level: Easy

Time required: 3 minutes

Scheduler by Quickwork as a trigger--for triggering the journey
IBM Watson Tone Analyzer: Action

Configuring the trigger

Under the Event section, choose the Scheduler by Quickwork app from the drop-down menu in the Apps field present right below the New Trigger button.
Select the trigger event, New scheduled event, from the drop-down menu in the Triggers field.
Set the Interval as per your preference based on how many times you want to execute the journey.
Set the date and time of your choice in the Start At field and keep the Custom Payload field empty:

Configuring IBM Watson Tone Analyzer action

Under the Steps section, click on the Simple Action button and choose the IBM Watson Tone Analyzer service from the drop-down menu in the Apps field.
Select the Analyze emotions or language tones from text action from the drop-down menu in the Actions field.
Click the Link an account button to establish a new connection with IBM Watson Tone Analyzer service. You can also connect an existing account if you have one.
The Text input field will open. Here, specify the text in the plain text format of which tonality and emotion you want to check in plain text format. E.g., I regret to announce that the launching of GSLV rocket has failed due to technical flaws. The mission is in the abort state until further notice:

Executing the journey

Save the changes done in the journey and click the Start Journey button. You'll be taken to the History tab automatically. Click on the record that just got created. In the Steps section, click the IBM Watson Tone Analyzer action bar to expand and observe the Output block to check the output:

You'll see a list of tones and emotions that the IBM Watson Tone Analyser service checks for a text. After analyzing more precisely, it also returns an output with the dominant language, emotional, and, social tone. The specified example text was sad, open, and analytical which can be seen in the result.