Guide-linked quiz · Medium Level
How to Spot Fake Product Reviews With AI Quiz
Tests spotting fake-review patterns like timing bursts and review hijacking, the limits of AI text detectors, and using AI to summarize genuine feedback.
Question 1 of 8
A kitchen knife listing is full of reviews about a phone case. What is this pattern called?
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- A kitchen knife listing is full of reviews about a phone case. What is this pattern called?
- Incentivized reviewing
- Review suppression
- Verified purchasing
- Review hijacking
- Why does the guide say patterns across many reviews are more reliable than judging one review?
- Platforms delete every fake review within a day
- AI can write fluent, specific-sounding text, so single reviews are hard to judge
- Individual reviews are always genuine
- Only the first review on a listing matters
- Which rating distribution does the guide treat as a warning sign?
- Almost only five-star and one-star reviews, with little in between
- A mix of ratings concentrated around four stars
- Reviews spread evenly over several years
- Mostly three-star reviews with detailed text
- Which star level does the guide say is often most informative when using AI to summarize real feedback?
- Five-star
- One-star
- Three-star
- Unrated reviews
- What does the guide say about using AI text detectors to prove a review was machine-written?
- They are required by the FTC rule
- They are the most reliable single signal
- They only work on five-star reviews
- They are unreliable and flag human writing as AI
- Why doesn't an AI-generated summary of reviews automatically filter out fakes?
- It summarizes whatever reviews it is given, fakes included
- It only reads verified purchases
- It deletes suspicious reviews before summarizing
- It is written by the seller
- How does the guide describe reviews from a disclosed program like Amazon Vine?
- Fake reviews that break the FTC rule
- Reviews written by AI
- Not fake, since they are labeled, but they may lean positive
- Always negative, to seem balanced
- According to the guide, how do platforms mainly detect fake reviews?
- By reading each review for spelling errors
- Through behavior and metadata such as account history, timing bursts and device overlaps
- By asking reviewers to confirm by email
- By removing all five-star reviews
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