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 10 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 9 *
( 88 [Dickey County] *
1 [Sanborn Fire Insurance Map from Ellendale] *
1 [Forbes, North Dakota] *
1 [Fullerton, North Dakota] *
4 [Ludden, North Dakota] *
4 [Monango, North Dakota] *
9 [North Dakota Highway 11] *
4 [Postcards of Dickey County, North Dakota] *
1 [Animals of Kulm Wetland Management District] *
1 [Flora of Kulm Wetland Management District]
)
= 456.2K
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.38 [Dickey County] *
1 [Sanborn Fire Insurance Map from Ellendale] *
1 [Forbes, North Dakota] *
1 [Fullerton, North Dakota] *
1 [Ludden, North Dakota] *
1 [Monango, North Dakota] *
1 [North Dakota Highway 11] *
1 [Postcards of Dickey County, North Dakota] *
1 [Animals of Kulm Wetland Management District] *
1 [Flora of Kulm Wetland Management District]
)
= 1.38
Outbound
3
Tags on post
Inbound
3
Posts tagging this
Connections
10
Total nodes
Base Node Strength
9
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Dickey County 71.54%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)