Sentiment analysis helps you understand how participants feel based on analysis done on the the response they provide on open end text or open end video questions. We use an API that analyzes text and labels the overall tone. It supports multiple major languages, but all text in one analysis must be in the same language
Sentiment Categories
For every text, It returns one of four results:
Positive – The text shows a positive feeling
Negative – The text shows a negative feeling
Mixed – The text contains both positive and negative feelings
Neutral – The text does not show strong positive or negative feelings
Sentiment Score (Sentiment percentage)
A sentiment score represents how likely it is that a piece of text belongs to each sentiment category. The percentages show how confident the system is about the possible sentiment.
For every piece of text (like a video transcript or open-ended response), the system checks all four sentiment category and then gives a %
For example, Positive: 95% means that the system is very confident (95%) the text is positive (There’s a very small chance it could be negative, neutral, or mixed)