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, 6) = 6
$outbound = max(1, 6) = 6
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 6 * 6 = 36
Base_Influence (IV) = $inbound / $outbound = 6 / 6 = 1
// 3. Exponential Network Values (accumulating 14 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 36 *
( 15 [leipzig] *
1 [Chicago School of Law] *
1 [Herald Square Theatre] *
1 [Oskaloosa College] *
1 [University of Connecticut] *
25 [University of Music and Theatre Leipzig] *
25 [Yale University] *
4 [christian gottlob neefe] *
4 [Günter Raphael] *
4 [Hochschule für Musik und Theater „Felix Mendelssohn Bartholdy“ Leipzig] *
4 [Douglas Moore] *
25 [Aaron Jay Kernis] *
9 [Alexei Navalny] *
1 [Skull and Bones]
)
= 19.44B
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.67 [leipzig] *
1 [Chicago School of Law] *
1 [Herald Square Theatre] *
1 [Oskaloosa College] *
1 [University of Connecticut] *
1 [University of Music and Theatre Leipzig] *
1 [Yale University] *
1 [christian gottlob neefe] *
1 [Günter Raphael] *
1 [Hochschule für Musik und Theater „Felix Mendelssohn Bartholdy“ Leipzig] *
1 [Douglas Moore] *
1 [Aaron Jay Kernis] *
1 [Alexei Navalny] *
1 [Skull and Bones]
)
= 1.67
Outbound
6
Tags on post
Inbound
6
Posts tagging this
Connections
14
Total nodes
Base Node Strength
36
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)