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 17 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 16 *
( 56 [Bolama] *
196 [Guinea-Bissau] *
9 [Bafatá] *
1 [Biombo] *
4 [Gabu] *
1 [Oio] *
1 [Quinara] *
1 [Tombali] *
1 [Guiné-Bissau] *
1 [Guinea-Bissau by media type] *
1 [Objects in Guinea-Bissau] *
1 [Playgrounds in Guinea-Bissau] *
1 [Society of Guinea-Bissau] *
1 [Wikimedia movement in Guinea-Bissau] *
1 [Forte de Cacheu] *
1 [Memorial da Escravatura e do Tráfico Negreiro] *
1 [Parque Natural dos Tarrafes do Rio Cacheu]
)
= 6.32M
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.14 [Bolama] *
1 [Guinea-Bissau] *
1 [Bafatá] *
1 [Biombo] *
1 [Gabu] *
1 [Oio] *
1 [Quinara] *
1 [Tombali] *
1 [Guiné-Bissau] *
1 [Guinea-Bissau by media type] *
1 [Objects in Guinea-Bissau] *
1 [Playgrounds in Guinea-Bissau] *
1 [Society of Guinea-Bissau] *
1 [Wikimedia movement in Guinea-Bissau] *
1 [Forte de Cacheu] *
1 [Memorial da Escravatura e do Tráfico Negreiro] *
1 [Parque Natural dos Tarrafes do Rio Cacheu]
)
= 1.14
Outbound
4
Tags on post
Inbound
4
Posts tagging this
Connections
17
Total nodes
Base Node Strength
16
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Guinea-Bissau 66.67%Bolama 19.05%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)
