Urban 75 World Cup 2026 Reaction Analysis

Recorded reactions received

Whose posts attracted acknowledgement?

Compare total response, reaction rate and breadth. These are complementary indicators: volume rewards sustained contribution, while rates ask how frequently or strongly a contributor’s posts drew a recorded reaction.

Important boundaryThe forum displayed abbreviated reaction bars, so every figure is a lower-bound count. We know which post and author received reactions, but not the complete identities of those reacting or the reaction types; this page therefore makes no claims about top givers, reciprocity or liker–recipient relationships.

—Recorded reactions

Posts with a reaction

—Recipients

—Reactions per 100 posts

Rank contributors by Minimum posts

Select a contributor to compare their recorded reaction volume, rate and breadth.

Activity and recognition

Did posting more usually mean receiving more?

Each circle is a contributor. Logarithmic axes keep occasional and prolific contributors visible together; selecting a circle connects the chart to the same recipient details used above.

Select a circle to inspect a contributor.

Distribution of recognition

How concentrated were recorded reactions?

The Lorenz curve compares contributors’ cumulative share with their cumulative share of reactions. The companion chart keeps the much larger set of posts with no recorded reaction visible.

Lorenz curve

The diagonal is perfect equality. A deeper bow indicates that a smaller share of contributors received more of the recorded reaction volume.

Reactions recorded per post

Posts grouped by their stored lower-bound reaction count. Bar height represents the share of all posts.

Professional and academic context

How to interpret the measures

Separate reach from intensity

Community analysts should not treat a single leaderboard as a complete measure of value. Total reactions are a weighted response volume, while reacted-post share measures breadth and reactions per post adjusts for contribution opportunity.

Weighted-network research similarly distinguishes the number of connections from their strength rather than collapsing both into one measure. This dataset lacks complete sender identities, so it applies that distinction only to received response—not to a social network. Opsahl, Agneessens and Skvoretz (2010)

Protect rankings from tiny samples

Raw rates can be extreme when someone wrote only one or two posts. The adjusted view uses a Gamma–Poisson empirical-Bayes estimate, gently drawing uncertain rates towards the corpus average while leaving contributors with substantial evidence largely unchanged.

This follows the established ranking principle that shrinkage should depend on measurement precision. It reduces small-sample volatility without turning the result into a judgement of post quality. Laird and Louis (1989)

Methods and limitations