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How does the system determine sentiment score and polarity? When I look in Text IQ, it will say the comment is a -10 sentiment, but I read the comment, it's not negative at all. What are the words that it tracks that to determine if it's positive or negative? Is there a way to map or weight the sentiment similar to Response Weighting?
Best answer by Appzk
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Brief below:
For most Text iQ analysis, the question text is not relevant to the sentiment of the answer (e.g. “Why did you give us that score?”). However, occasionally the framing of the question will imply a sentiment for the answer (e.g. “What’s one thing we could improve about our product?”). In these cases, Text iQ needs both the question and the answer to make an accurate prediction of sentiment. For example, if the question was, “What do you love about our company?” then unless the answer is explicitly negative (e.g. “Nothing, you suck in every way”) then the sentiment of the response is probably positive, even if the answer text on its own appears neutral (e.g. “pricing”). This Sentiment Analysis update incorporates the question text, if available, in the sentiment analysis so that the predicted sentiment is as accurate as possible.
This model also now takes sentiment edits into account in order to learn how to better assign sentiments in the future. However, please note that these edits do not immediately affect the sentiment assignment of projects in your account. Instead, these edits are periodically analyzed across all Qualtrics users and used to improve the sentiment analysis model as a whole.
Reference link: https://www.qualtrics.com/support/survey-platform/data-and-analysis-module/text-iq/sentiment-analysis/
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