An affect is a word or a group of words identified in a message. For each word or group of words detected, a tone is attached: positive or negative.
This article will cover:
Understanding Affects
Affects are detected automatically thanks to machine learning technology. The Algorithm is based on a large organized dataset annotated manually. The tool will collect the expressions with the highest occurrence.
The tone is made thanks to the sentiment classifier (positive or negative) based on the expressions found within post contents.
Finding Affects in Radarly
In your filter bar, Textual & thematic analysis section > Affects.
Then depending on your goals, you can select the positive or negative affects :
Note: Affects can also be viewed in Posts & Analytics page by creating a personalized view in the workspace settings (need to be an administrator).
Benefits of Affects
Understanding of opinions expressed about a brand, product or a subject and more precisely how the authors qualify them: positive or negative.
Tag cloud allows you to quickly understand which expressions are most used in publications. The larger the size of the affect, the higher the occurrence.
This feature allows to get information about opinions in long text documents.
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