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, 7) = 7
$outbound = max(1, 5) = 5
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 7 * 5 = 35
Base_Influence (IV) = $inbound / $outbound = 7 / 5 = 1.4
// 3. Exponential Network Values (accumulating 9 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 35 *
( 4 [Hartnell College] *
4 [Sanborn Fire Insurance Map from Salinas, Monterey County, California] *
4 [Dorothy's Soup Kitchen] *
4 [Postcards of Salinas, California published by Brück & Sohn] *
1 [National Steinbeck Center] *
1 [Salinas Navy Week] *
1 [SVMH Medical Museum] *
1 [2020 in Salinas] *
56 [Salinas]
)
= 501.8K
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1.4 *
( 1 [Hartnell College] *
1 [Sanborn Fire Insurance Map from Salinas, Monterey County, California] *
1 [Dorothy's Soup Kitchen] *
1 [Postcards of Salinas, California published by Brück & Sohn] *
1 [National Steinbeck Center] *
1 [Salinas Navy Week] *
1 [SVMH Medical Museum] *
1 [2020 in Salinas] *
0.875 [Salinas]
)
= 1.23
Outbound
7
Tags on post
Inbound
5
Posts tagging this
Connections
9
Total nodes
Base Node Strength
35
Base Node Influence
1.4
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Salinas 50.45%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)
2020 in Salinas, California
BROKEN LINK