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FanEdit Ranking and Research Methodology

FanEdit organizes public edit, creator, hashtag, sound, community, and campaign records into crawlable archives. Rankings use stored performance signals; research pages publish dated snapshots and state what the dataset includes, excludes, and cannot prove.

By FanEdit Editorial Team · Updated Aug 17, 2026

Home

Fan edits, creator rankings, and Hall of Fame discovery live in one public category surface.

Engine

VibeEdit is the AI-native editing system behind footage understanding and edit workflow acceleration.

Campaigns

Brands use FanEdit to source editors, brief launch waves, review creative, and learn from fandom response.

01

Public data and entity relationships

FanEdit stores public post and creator information and connects edits to creators, hashtags, sounds, contests, and communities when those relationships are available.

Public platform metrics can change

Unavailable or private records may disappear

Not every platform or edit is represented

02

Impact score

The current impact calculation combines comments, likes, and views as: 100 × comments + 0.001 × likes + views ÷ 100,000, rounded to two decimal places. The weighting is a FanEdit discovery heuristic, not a universal measure of artistic quality or business value.

Comments receive the strongest weight

Likes and views provide additional scale signals

Rankings should be paired with manual creative review

03

Research snapshots

A dated research page freezes its reported counts and scope so readers can cite a stable statement even while live archives continue to update.

Every snapshot names its date

Every snapshot distinguishes tracked records from the global market

Corrections should be documented rather than silently backdated

04

Known limitations

Public platform metrics can contain delays, removals, duplicates, regional differences, and inconsistent definitions. Correlation in the archive does not establish why an edit performed or what business outcome it caused.

No claim of complete market coverage

No claim that rankings equal creative quality

No causal campaign claim without supporting attribution data

What to read next

How FanEdit works behind the page.

The About section explains the practical pieces behind FanEdit: how footage becomes searchable, how AI editing helps without flattening taste, and how repeatable edit formats become campaigns.

For brands

Campaigns need taste and operations.

FanEdit is built for the messy middle between a social brief and culture: sourcing fan editors, preparing approved assets, shaping creative guardrails, and reviewing short-form work without flattening what makes fan edits feel native.