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, 2) = 2
$outbound = max(1, 2) = 2
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 2 * 2 = 4
Base_Influence (IV) = $inbound / $outbound = 2 / 2 = 1
// 3. Exponential Network Values (accumulating 20 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 4 *
( 42 [UCLA] *
224 [Second Viennese School] *
1 [virginia woolf] *
9 [Alexander Zemlinskey 1871] *
4 [Vienna Conservatory] *
25 [Lars Erik Larsson] *
1 [Leon Kirchner] *
4 [Alexander von Zemlinsky] *
36 [Alban Berg] *
4 [Robert Gerhard] *
4 [Nikos Skalkottas] *
4 [Hanns Eisler] *
25 [Theodor W. Adorno] *
1 [Stefania Turkewich] *
1 [Oscar Levant] *
1 [Egon Wellesz] *
1 [Earl Kim] *
1 [Dika Newlin] *
1 [Charles Rosen] *
342 [Arnold Schoenberg]
)
= 2.67 x 10^15
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.17 [UCLA] *
1.14 [Second Viennese School] *
1 [virginia woolf] *
1 [Alexander Zemlinskey 1871] *
1 [Vienna Conservatory] *
1 [Lars Erik Larsson] *
1 [Leon Kirchner] *
1 [Alexander von Zemlinsky] *
1 [Alban Berg] *
1 [Robert Gerhard] *
1 [Nikos Skalkottas] *
1 [Hanns Eisler] *
1 [Theodor W. Adorno] *
1 [Stefania Turkewich] *
1 [Oscar Levant] *
1 [Egon Wellesz] *
1 [Earl Kim] *
1 [Dika Newlin] *
1 [Charles Rosen] *
0.9474 [Arnold Schoenberg]
)
= 1.26
Outbound
2
Tags on post
Inbound
2
Posts tagging this
Connections
20
Total nodes
Base Node Strength
4
Base Node Influence
1
Strength Share (vs Direct Neighbours)
0.54%
(2.67 × 1015 overall)
Dominant nodes (excluded from chart)Arnold Schoenberg 46.53%Second Viennese School 30.48%UCLA 5.71%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)
