Scoring engine
The scoring engine is what makes the MBER feed different from scrolling X directly. It ranks every post by genuine signal, so the strongest content rises to the top no matter how big or small the account is.
Why raw numbers mislead
If you sort by likes, big accounts always win. A post with five thousand likes from a huge account will outrank a post with eighty likes from a small one, even when the smaller post earned far more attention relative to its reach. Raw engagement measures audience size as much as it measures quality.
MBER scores for quality instead. A sharp post from a smaller account can, and often does, outrank a viral post from a megaphone.
What MBER rewards
Without exposing the recipe, the scoring engine balances a few ideas:
- Substance. How much real engagement a post earned.
- Efficiency. How much engagement it earned relative to how many people saw it. This is the great equalizer for smaller accounts.
- Reach. How many people it got in front of, with diminishing returns so reach alone cannot dominate.
The result is a single ranking that surfaces quality regardless of follower count.
Score pills: ENG, VRL, and QUAL
Each post also carries three pills, scored from 0 to 10:
- ENG, overall engagement,
- VRL, virality or shareability,
- QUAL, depth of interest.
The important detail: these pills are relative to the posts you are currently looking at, not to the entire database. A 10 means "near the top of this view." When you change filters, the meaning shifts with them, by design. The pill answers "how does this compare to what is in front of me right now."
When your current view is too small to compare fairly, MBER shows a neutral mark instead of a misleading number.
This page explains the philosophy behind ranking. The exact scoring math is part of what makes MBER work, and stays under the hood.
Related
- Scraping engine: how posts get collected in the first place.
- Categorization engine: how posts get sorted by topic.