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Glossary

Review sentiment analysis

Also called: opinion mining

Definition

Review sentiment analysis sorts reviews by the mood they show, such as good, bad or mixed.

Star ratings give you a rough mood, but they miss a lot. A 4-star review can still hold a sharp complaint. A 2-star review might praise the design but hate the price. Sentiment analysis reads the words, not just the stars.

Simple tools count positive and negative words. AI models go further. They can tell the mood about each topic in a review, like "love the design, hate the ads."

Why it matters

Sentiment by topic tells you what to protect and what to fix. If talk about "sync" turns more negative after a release, you know where to look first. A free App Teardown shows this for any app's recent reviews.

Example

Review: "Great app, but the new update logs me out all the time."

Overall: mixed. The app as a whole: positive. Login: negative.

  • Feedback tagging Feedback tagging means labeling each piece of feedback with a topic, like bug or price, so you can count themes.
  • Voice of the customer (VoC) Voice of the customer (VoC) means gathering what customers say, in their own words, and using it to guide your choices.
  • App Store rating An App Store rating is the 1 to 5 star score people give an app, shown as one overall score per country.
  • Competitive analysis Competitive analysis means studying rival apps to find where they win, where they fail, and where you can stand out.

Learn more

Updated by the Synthiya team. See all terms.

See what users say about any app

Paste an App Store link or type a name. Synthiya reads the latest reviews and sums up what people love, hate and want. It is free.