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, 5) = 5
$outbound = max(1, 5) = 5
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 5 * 5 = 25
Base_Influence (IV) = $inbound / $outbound = 5 / 5 = 1
// 3. Exponential Network Values (accumulating 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 25 *
( 35 [ঢাকা] *
72 [Dhaka] *
90 [Bangladesh] *
4 [Objects in Dhaka] *
4 [Public services in Dhaka] *
4 [Sports in Dhaka] *
1 [Zero Point of Dhaka] *
1 [Architectural elements in Dhaka] *
1 [Landscape architecture in Dhaka] *
1 [Structures in Dhaka] *
2 [Society of Dhaka]
)
= 725.76M
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.4 [ঢাকা] *
1.13 [Dhaka] *
1.11 [Bangladesh] *
1 [Objects in Dhaka] *
1 [Public services in Dhaka] *
1 [Sports in Dhaka] *
1 [Zero Point of Dhaka] *
1 [Architectural elements in Dhaka] *
1 [Landscape architecture in Dhaka] *
1 [Structures in Dhaka] *
0.5 [Society of Dhaka]
)
= 0.875
Outbound
5
Tags on post
Inbound
5
Posts tagging this
Connections
11
Total nodes
Base Node Strength
25
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Bangladesh 37.50%Dhaka 30.00%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)