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, 4) = 4
$outbound = max(1, 4) = 4
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 4 * 4 = 16
Base_Influence (IV) = $inbound / $outbound = 4 / 4 = 1
// 3. Exponential Network Values (accumulating 13 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 16 *
( 100 [Filtry Lindleya] *
1 [Plaques to William Lindley] *
1 [Wasserturm der Stadtwasserkunst in Hamburg-Rothenburgsort] *
1 [Wasserwerk Baursberg] *
16 [William Heerlein Lindley] *
1 [Monument to Sokrates Starynkiewicz in Warsaw] *
1 [Rapid sand filters in Warsaw] *
1 [Reliefs in Lindley Filter Station in Warsaw] *
1 [Slow sand filters in Warsaw] *
1 [Monumental horse-chestnut in Warsaw filtre station] *
1 [Museum of Water and Sewer Systems in Warsaw] *
1 [Water towers of Filtry Lindleya] *
1 [Former boiler house of Lindley's Filter Station]
)
= 25.6K
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1 [Filtry Lindleya] *
1 [Plaques to William Lindley] *
1 [Wasserturm der Stadtwasserkunst in Hamburg-Rothenburgsort] *
1 [Wasserwerk Baursberg] *
1 [William Heerlein Lindley] *
1 [Monument to Sokrates Starynkiewicz in Warsaw] *
1 [Rapid sand filters in Warsaw] *
1 [Reliefs in Lindley Filter Station in Warsaw] *
1 [Slow sand filters in Warsaw] *
1 [Monumental horse-chestnut in Warsaw filtre station] *
1 [Museum of Water and Sewer Systems in Warsaw] *
1 [Water towers of Filtry Lindleya] *
1 [Former boiler house of Lindley's Filter Station]
)
= 1
Outbound
4
Tags on post
Inbound
4
Posts tagging this
Connections
13
Total nodes
Base Node Strength
16
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Filtry Lindleya 69.93%William Heerlein Lindley 11.19%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)