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 20 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 16 *
( 16 [Wanja Mues] *
289 [Unsere Hagenbecks] *
25 [Beatrice Kessler] *
4 [Charles Regnier] *
1 [Christian Dalesch] *
1 [Daphne Wagner] *
16 [Dirk Dautzenberg] *
1 [Dirk Martens] *
1 [Franz Josef Steffens] *
1 [Giulia Follina] *
1 [Lonny Kellner] *
9 [Nicole Boguth] *
16 [Otto Tausig] *
16 [Rainer Rudolph] *
1 [Tilly Lauenstein] *
1 [Traudel Sperber] *
1 [Jörg Pleva] *
1 [Lisa Falk - Eine Frau für alle Fälle] *
1 [Philadelphia, ich bin da!] *
1 [Tod eines Mädchens]
)
= 272.73B
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1 [Wanja Mues] *
1 [Unsere Hagenbecks] *
1 [Beatrice Kessler] *
1 [Charles Regnier] *
1 [Christian Dalesch] *
1 [Daphne Wagner] *
1 [Dirk Dautzenberg] *
1 [Dirk Martens] *
1 [Franz Josef Steffens] *
1 [Giulia Follina] *
1 [Lonny Kellner] *
1 [Nicole Boguth] *
1 [Otto Tausig] *
1 [Rainer Rudolph] *
1 [Tilly Lauenstein] *
1 [Traudel Sperber] *
1 [Jörg Pleva] *
1 [Lisa Falk - Eine Frau für alle Fälle] *
1 [Philadelphia, ich bin da!] *
1 [Tod eines Mädchens]
)
= 1
Outbound
4
Tags on post
Inbound
4
Posts tagging this
Connections
20
Total nodes
Base Node Strength
16
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Unsere Hagenbecks 68.97%Beatrice Kessler 5.97%Wanja Mues 3.82%Dirk Dautzenberg 3.82%Otto Tausig 3.82%Rainer Rudolph 3.82%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)