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, 9) = 9
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 10 * 9 = 90
Base_Influence (IV) = $inbound / $outbound = 10 / 9 = 1.1111
// 3. Exponential Network Values (accumulating 10 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 90 *
( 6 [HKICC Lee Shau Kee School of Creativity, HKSC] *
6 [HKU] *
1 [HKFYG Lee Shau Kee College] *
1 [HKFYG Lee Shau Kee Primary School] *
1 [Lee Shau Kee Foundation] *
1 [Shun Tak Fraternal Association Lee Shau Kee College] *
9 [HKICC Lee Shau Kee School of Creativity] *
4 [Lee Shau Kee Lecture Centre, HKU] *
6 [HKSC] *
2 [Lee Shau Kee Lecture Centre]
)
= 1.4M
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1.1111 *
( 1.5 [HKICC Lee Shau Kee School of Creativity, HKSC] *
1.5 [HKU] *
1 [HKFYG Lee Shau Kee College] *
1 [HKFYG Lee Shau Kee Primary School] *
1 [Lee Shau Kee Foundation] *
1 [Shun Tak Fraternal Association Lee Shau Kee College] *
1 [HKICC Lee Shau Kee School of Creativity] *
1 [Lee Shau Kee Lecture Centre, HKU] *
0.6667 [HKSC] *
0.5 [Lee Shau Kee Lecture Centre]
)
= 0.8334
Outbound
10
Tags on post
Inbound
9
Posts tagging this
Connections
10
Total nodes
Base Node Strength
90
Base Node Influence
1.1111
Strength Share (vs Direct Neighbours)
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)