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, 8) = 8
$outbound = max(1, 6) = 6
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 8 * 6 = 48
Base_Influence (IV) = $inbound / $outbound = 8 / 6 = 1.3333
// 3. Exponential Network Values (accumulating 8 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 48 *
( 56 [Slezské zemské muzeum] *
4 [Antonín Šimčík] *
9 [Log cabin of Petr Bezruč] *
4 [Museum of the fortifications Hlučín] *
4 [Národní památník války] *
4 [Slezské zemské muzeum - hlavní budova] *
49 [Petr Bezruč] *
2 [QRpedia codes at Silesian Museum Opava]
)
= 606.93M
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1.3333 *
( 1.14 [Slezské zemské muzeum] *
1 [Antonín Šimčík] *
1 [Log cabin of Petr Bezruč] *
1 [Museum of the fortifications Hlučín] *
1 [Národní památník války] *
1 [Slezské zemské muzeum - hlavní budova] *
1 [Petr Bezruč] *
0.5 [QRpedia codes at Silesian Museum Opava]
)
= 0.7619
Outbound
8
Tags on post
Inbound
6
Posts tagging this
Connections
8
Total nodes
Base Node Strength
48
Base Node Influence
1.3333
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Slezské zemské muzeum 31.11%Petr Bezruč 27.22%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)
Exhibits in the Silesian Museum
BROKEN LINK