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, 3) = 3
$outbound = max(1, 3) = 3
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 3 * 3 = 9
Base_Influence (IV) = $inbound / $outbound = 3 / 3 = 1
// 3. Exponential Network Values (accumulating 14 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 9 *
( 168 [Neuquén] *
1 [Estadio Ruca Che] *
1 [FaSinPat] *
36 [Independiente de Neuquén] *
1 [MNBA Neuquén] *
1 [Neuquén Cathedral] *
1 [Neuquén River in Neuquén] *
1 [Neuquén train station] *
1 [Presidente Perón International Airport] *
1 [Theaters in Neuquén] *
1 [Universidad Nacional del Comahue] *
4 [Equestrian statue of José de San Martín, Neuquén] *
1 [Neuquén-Cipolletti railway bridges] *
1 [Neuquén-Cipolletti road bridges]
)
= 217.7K
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.17 [Neuquén] *
1 [Estadio Ruca Che] *
1 [FaSinPat] *
1 [Independiente de Neuquén] *
1 [MNBA Neuquén] *
1 [Neuquén Cathedral] *
1 [Neuquén River in Neuquén] *
1 [Neuquén train station] *
1 [Presidente Perón International Airport] *
1 [Theaters in Neuquén] *
1 [Universidad Nacional del Comahue] *
1 [Equestrian statue of José de San Martín, Neuquén] *
1 [Neuquén-Cipolletti railway bridges] *
1 [Neuquén-Cipolletti road bridges]
)
= 1.17
Outbound
3
Tags on post
Inbound
3
Posts tagging this
Connections
14
Total nodes
Base Node Strength
9
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Neuquén 73.68%Independiente de Neuquén 15.79%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)