How is this calculated?
The math continuously tracks how strongly this post is connected to the rest of the network. Every tag forms a 2-way link. The base stats determine personal node strength, and the pie charts below show this node's share against its direct neighbours.
// 1. Base variables (floored at 1 to prevent zero-multiplication math errors)
$inbound = max(1, 1) = 1
$outbound = max(1, 1) = 1
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 1 * 1 = 1
Base_Influence (IV) = $inbound / $outbound = 1 / 1 = 1
// 3. Exponential Network Values (accumulating 25 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 1 *
( 8 [Swiss Confederation] *
650 [Switzerland] *
100 [Zugdidi] *
1 [Aargau] *
1 [Appenzell Ausserrhoden] *
1 [Appenzell Innerrhoden] *
1 [Basel-Landschaft] *
4 [Basel-Stadt] *
1 [Bern] *
1 [Glarus] *
1 [Graubünden;Grisons] *
1 [Jura] *
1 [Luzern] *
1 [Neuchâtel] *
1 [Nidwalden] *
1 [Obwalden] *
1 [Schwyz] *
1 [Solothurn] *
1 [St. Gallen] *
1 [Thurgau] *
1 [Ticino] *
16 [Uri] *
1 [Valais] *
1 [Vaud] *
4 [Zug]
)
= 133.12M
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 2 [Swiss Confederation] *
1.04 [Switzerland] *
1 [Zugdidi] *
1 [Aargau] *
1 [Appenzell Ausserrhoden] *
1 [Appenzell Innerrhoden] *
1 [Basel-Landschaft] *
1 [Basel-Stadt] *
1 [Bern] *
1 [Glarus] *
1 [Graubünden;Grisons] *
1 [Jura] *
1 [Luzern] *
1 [Neuchâtel] *
1 [Nidwalden] *
1 [Obwalden] *
1 [Schwyz] *
1 [Solothurn] *
1 [St. Gallen] *
1 [Thurgau] *
1 [Ticino] *
1 [Uri] *
1 [Valais] *
1 [Vaud] *
1 [Zug]
)
= 2.08
Outbound
1
Tags on post
Inbound
1
Posts tagging this
Connections
25
Total nodes
Base Node Strength
1
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Switzerland 81.05%Zugdidi 12.47%Uri 2.00%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)
