Example generated by Viral OS
How to Spot a Fake Review in 30 Seconds
Educational · Gap → Why → Explain → Apply → Takeaway · Facebook Reels · English · ~30s · 72 words
0:00-0:05 · Hook
You’re likely missing the one linguistic signal that exposes a fraud.
Visual: Phone screen, 5-star review on a product page. A highlighter box slowly sweeps over the first sentence. Big burned-in text from frame 1.
Edit: Hard open on the phone screen with the 5-star review already in frame and the burned-in headline visible from frame 1. A yellow highlighter box sweeps slowly across the first sentence over about 3 seconds. Add a gentle 5% push-in on the sentence. No cut inside this beat. Hold a short pause after 'first sentence' so the gap lands.
0:05-0:09 · Why
Five stars can be bought; the score alone proves little.
Visual: Star rating zooms in, then a small price tag icon appears next to the stars. Soft pop on the price tag.
Edit: Cut to the star rating and do a controlled zoom into the five stars (about 110% over 1.5s). A small price tag icon fades in beside the stars right after 'bought'. Hold the final frame for a beat after 'proves little' so the idea sinks in.
0:09-0:13 · Explain
Fake reviews focus on feelings. "Amazing product" could fit anything.
Visual: Same generic review pasted under three unrelated products (a blender, a hotel, a phone case). Each gets a red 'fits anything' tag.
Edit: Show the same generic review pasted under three products in sequence (blender, hotel, phone case), about 1.2s each. Use simple straight cuts timed to the sentence rhythm. Stamp a red 'fits anything' tag on each. On the third product, hold a beat and keep the review text in the same screen position so the viewer sees it is identical. No whip transitions.
0:13-0:18 · Explain
Real reviews name specific uses or flaws. Vague ones name nothing.
Visual: Split screen on one coffee mug listing. Left: "Amazing product, highly recommend" with a red 'fits anything' tag. Right: "Lid cracked after a week, but it kept coffee hot on my commute." Three details (flaw, use, moment) highlight in the accent colour with a controlled zoom on the right card.
Edit: Whoosh reveal of the second review sliding over the first. Then do a controlled zoom (about 115%) on the review text as each key detail is highlighted in the accent colour, one at a time: 'Lid cracked after a week', 'kept coffee hot', 'on my commute'. Match each highlight to the words 'use', 'flaw', 'moment' as they are spoken. Hold the final highlighted frame for a beat before the next cut.
0:18-0:24 · Apply
Tap the profile. Praise for a gym and a vacuum? That's one review, pasted everywhere.
Visual: Screen recording: finger taps the reviewer's name. The profile shows 5-star reviews for a gym, a vacuum and a restaurant, each reading "Amazing, highly recommend". The three identical lines highlight, then a yellow warning mark appears.
Edit: Cut to a clean screen recording: a finger taps the reviewer's name. Show Profile A ('1 review') for about 2s, then Profile B (long list of 5-star reviews for a gym, a vacuum and a restaurant) for about 3s. Add a gentle scroll on Profile B so the unrelated items are visible. Place a yellow warning mark on each profile as it appears. Use a small tap-circle overlay so the action is easy to follow.
0:24-0:30 · Takeaway
If a review fits any product, trust it less. Save this for your next purchase.
Visual: A single question card: "Could this fit any product?" The vague mug review slides in, a check ticks, and the card turns red with 'trust less'. Final card with the one-line rule and 'Save this for your next purchase' in large text.
Edit: Show three checkboxes ticking one after another, timed to the spoken phrases 'vague wording', 'a thin profile' and 'odd timing'. Then a slow, controlled push-in on the checklist as 'trust it less' is spoken. Cut to the final card and hold it for the last 2 seconds with the takeaway and 'Save this for your next purchase' in large text. Leave a clean, still frame at the end with no extra motion.
Editing blueprint summary
visual direction: Clean, bright, screen-first look. Almost everything is a phone screen or a review card on a plain light background, so the viewer sees exactly what the voice describes. One accent colour for the key terms, a red tag for generic reviews and a yellow warning mark for profile red flags. Use consistent framing, with the review text in the same area of the screen across beats. Keep the tone neutral and teacher-like, with no dramatic lighting, face cam or reaction shots. Use only mock or anonymised reviews and profiles, with no real names or photos.
editing: - Balanced pace: roughly one visual change per beat, with no cut every 2 seconds and no bass hits. - Use controlled zooms (5-15%) only on the key detail: the first sentence, the stars, the highlighted review details, the checklist. - Use straight cuts for comparisons and a single whoosh reveal for the real review. - Leave a brief pause after each key fact (after 'first sentence', 'proves little', 'warning') by holding the frame. - Burn in the headline from frame 1 and keep the final card still for the last 2 seconds.
music: Light, minimal, unobtrusive instrumental (soft keys or mellow plucks with a gentle pulse). Pick from the platform's licensed library, royalty-free or original music. Do not use a copyrighted track unless it is cleared for use.
captions: Full captions, clean sans-serif, bold weight, white text with a subtle shadow. Show 3-6 words at a time in sync with the voice. Key terms in the accent colour.
Why this works
- Timing feasibility: 72 words fits a 30-second read comfortably at about 2.4 words per second.
- Category consistency: It teaches a usable heuristic with examples and has no personal story.
- Natural language: Conversational, punchy lines suited to spoken delivery.
From the engine's own category evaluation. Scores are AI predictions, not real performance data.
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