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, 1) = 1
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 3 * 1 = 3
Base_Influence (IV) = $inbound / $outbound = 3 / 1 = 3
// 3. Exponential Network Values (accumulating 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 3 *
( 6 [Vilnius] *
121 [Lithuania] *
1 [Alytus] *
1 [Kaunas] *
1 [Klaipėda] *
1 [Marijampolė] *
1 [Šiauliai] *
1 [Tauragė] *
1 [Telšiai] *
1 [Utena] *
1 [Konstantinovo]
)
= 2.2K
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 3 *
( 1.5 [Vilnius] *
1 [Lithuania] *
1 [Alytus] *
1 [Kaunas] *
1 [Klaipėda] *
1 [Marijampolė] *
1 [Šiauliai] *
1 [Tauragė] *
1 [Telšiai] *
1 [Utena] *
1 [Konstantinovo]
)
= 4.5
Outbound
3
Tags on post
Inbound
1
Posts tagging this
Connections
11
Total nodes
Base Node Strength
3
Base Node Influence
3
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Lithuania 87.05%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)
Architecture of Panevėžys
BROKEN LINKPublic services in Panevėžys
BROKEN LINK
