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, 12) = 12
$outbound = max(1, 11) = 11
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 12 * 11 = 132
Base_Influence (IV) = $inbound / $outbound = 12 / 11 = 1.0909
// 3. Exponential Network Values (accumulating 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 132 *
( 1 [Environment in Hautes-Pyrénées] *
1 [Objects in Hautes-Pyrénées] *
1 [People in Hautes-Pyrénées] *
1 [Photographs of Hautes-Pyrénées] *
1 [Public services in Hautes-Pyrénées] *
1 [Science and technology in Hautes-Pyrénées] *
1 [Science and technology of Hautes-Pyrénées] *
1 [Society of Hautes-Pyrénées] *
1 [Sports in Hautes-Pyrénées] *
1 [Symbols of Hautes-Pyrénées] *
1 [Unidentified locations in Hautes-Pyrénées]
)
= 132
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1.0909 *
( 1 [Environment in Hautes-Pyrénées] *
1 [Objects in Hautes-Pyrénées] *
1 [People in Hautes-Pyrénées] *
1 [Photographs of Hautes-Pyrénées] *
1 [Public services in Hautes-Pyrénées] *
1 [Science and technology in Hautes-Pyrénées] *
1 [Science and technology of Hautes-Pyrénées] *
1 [Society of Hautes-Pyrénées] *
1 [Sports in Hautes-Pyrénées] *
1 [Symbols of Hautes-Pyrénées] *
1 [Unidentified locations in Hautes-Pyrénées]
)
= 1.09
Outbound
12
Tags on post
Inbound
11
Posts tagging this
Connections
11
Total nodes
Base Node Strength
132
Base Node Influence
1.0909
Strength Share (vs Direct Neighbours)
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)
Visitor attractions in Hautes-Pyrénées
BROKEN LINK