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, 2) = 2
$outbound = max(1, 3) = 3
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 2 * 3 = 6
Base_Influence (IV) = $inbound / $outbound = 2 / 3 = 0.6667
// 3. Exponential Network Values (accumulating 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 6 *
( 2 [Royal Library Garden, Copenhagen] *
4 [resources] *
49 [Copenhagen Business School] *
4 [Dermot O'Reilly] *
1 [Christina Markus Lassen] *
64 [David Heinemeier Hansson] *
1 [Faculty of Copenhagen Business School] *
1 [Leonard Seabrooke] *
9 [Copenhell] *
1 [Copenhagen bus line 666] *
1 [Copenhell 2011]
)
= 5.42M
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 0.6667 *
( 2 [Royal Library Garden, Copenhagen] *
1 [resources] *
1 [Copenhagen Business School] *
1 [Dermot O'Reilly] *
1 [Christina Markus Lassen] *
1 [David Heinemeier Hansson] *
1 [Faculty of Copenhagen Business School] *
1 [Leonard Seabrooke] *
1 [Copenhell] *
1 [Copenhagen bus line 666] *
1 [Copenhell 2011]
)
= 1.33
Outbound
2
Tags on post
Inbound
3
Posts tagging this
Connections
11
Total nodes
Base Node Strength
6
Base Node Influence
0.6667
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)David Heinemeier Hansson 44.76%Copenhagen Business School 34.27%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)
