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, 17) = 17
$outbound = max(1, 14) = 14
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 17 * 14 = 238
Base_Influence (IV) = $inbound / $outbound = 17 / 14 = 1.2143
// 3. Exponential Network Values (accumulating 23 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 238 *
( 4 [LVA] *
8 [Grodno] *
8 [Minsk] *
2 [Ventspils] *
6 [Gomel] *
4 [Brest] *
4 [Mogilev] *
9 [Vitebsk] *
1 [Daugavpils] *
4 [Jēkabpils] *
4 [Jūrmala] *
1 [Liepāja] *
4 [Rēzekne] *
1 [Riga] *
1 [Valmiera] *
1 [Ruba] *
1 [Viciebsk Castle] *
1 [Symbols of Jēkabpils] *
1 [Education in Jūrmala] *
1 [History of Rēzekne] *
48 [Belarus] *
2 [Hiking in Latvia] *
2 [Objects in Latvia]
)
= 1.29T
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1.2143 *
( 4 [LVA] *
2 [Grodno] *
2 [Minsk] *
2 [Ventspils] *
1.5 [Gomel] *
1 [Brest] *
1 [Mogilev] *
1 [Vitebsk] *
1 [Daugavpils] *
1 [Jēkabpils] *
1 [Jūrmala] *
1 [Liepāja] *
1 [Rēzekne] *
1 [Riga] *
1 [Valmiera] *
1 [Ruba] *
1 [Viciebsk Castle] *
1 [Symbols of Jēkabpils] *
1 [Education in Jūrmala] *
1 [History of Rēzekne] *
0.75 [Belarus] *
0.5 [Hiking in Latvia] *
0.5 [Objects in Latvia]
)
= 10.93
Outbound
17
Tags on post
Inbound
14
Posts tagging this
Connections
23
Total nodes
Base Node Strength
238
Base Node Influence
1.2143
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Belarus 13.48%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)
