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, 1) = 1
$outbound = max(1, 1) = 1
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 1 * 1 = 1
Base_Influence (IV) = $inbound / $outbound = 1 / 1 = 1
// 3. Exponential Network Values (accumulating 12 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 1 *
( 156 [Tucumán] *
4 [Casa Museo de la Ciudad San Miguel de Tucumán] *
4 [Cementerio del Oeste de Tucumán] *
4 [Escuela Congreso de Tucuman] *
4 [Facultad Regional Tucumán] *
4 [Nicolás Avellaneda Institute] *
81 [San Miguel de Tucumán] *
1 [Sports in San Miguel de Tucumán] *
1 [Symbols of San Miguel de Tucumán] *
4 [Universidad del Norte Santo Tomás de Aquino] *
1 [Universidad Nacional de Tucumán] *
4 [Casa de Tucumán]
)
= 207.03M
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.08 [Tucumán] *
1 [Casa Museo de la Ciudad San Miguel de Tucumán] *
1 [Cementerio del Oeste de Tucumán] *
1 [Escuela Congreso de Tucuman] *
1 [Facultad Regional Tucumán] *
1 [Nicolás Avellaneda Institute] *
1 [San Miguel de Tucumán] *
1 [Sports in San Miguel de Tucumán] *
1 [Symbols of San Miguel de Tucumán] *
1 [Universidad del Norte Santo Tomás de Aquino] *
1 [Universidad Nacional de Tucumán] *
1 [Casa de Tucumán]
)
= 1.08
Outbound
1
Tags on post
Inbound
1
Posts tagging this
Connections
12
Total nodes
Base Node Strength
1
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Tucumán 57.99%San Miguel de Tucumán 30.11%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)