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, 10) = 10
$outbound = max(1, 10) = 10
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 10 * 10 = 100
Base_Influence (IV) = $inbound / $outbound = 10 / 10 = 1
// 3. Exponential Network Values (accumulating 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 100 *
( 1 [Birgit Muggenthaler-Schmack] *
1 [Martin Duckstein] *
1 [Stefan Brunner] *
1 [Thomas Lindner] *
4 [Ally Storch] *
1 [Hubsi Widmann] *
1 [Matthias Richter] *
1 [Saskia Forkert] *
1 [Stefan Brunner (2)] *
1 [Anna Katharina Kränzlein] *
625 [Subway To Sally]
)
= 250K
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1 [Birgit Muggenthaler-Schmack] *
1 [Martin Duckstein] *
1 [Stefan Brunner] *
1 [Thomas Lindner] *
1 [Ally Storch] *
1 [Hubsi Widmann] *
1 [Matthias Richter] *
1 [Saskia Forkert] *
1 [Stefan Brunner (2)] *
1 [Anna Katharina Kränzlein] *
1 [Subway To Sally]
)
= 1
Outbound
10
Tags on post
Inbound
10
Posts tagging this
Connections
11
Total nodes
Base Node Strength
100
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Subway To Sally 84.69%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)
