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, 1) = 1
$outbound = max(1, 1) = 1
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 1 * 1 = 1
Base_Influence (IV) = $inbound / $outbound = 1 / 1 = 1
// 3. Exponential Network Values (accumulating 9 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 1 *
( 126 [George Mason University] *
1 [Antonin Scalia Law School] *
1 [Faculty of the George Mason University] *
1 [George Mason University athletics] *
1 [George Mason University Center for the Arts] *
1 [Photographs from George Mason University Life flickr photostream] *
1 [Rugby at George Mason University] *
1 [TEDxGMU] *
1 [Virginia State Route 383]
)
= 126
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1.56 [George Mason University] *
1 [Antonin Scalia Law School] *
1 [Faculty of the George Mason University] *
1 [George Mason University athletics] *
1 [George Mason University Center for the Arts] *
1 [Photographs from George Mason University Life flickr photostream] *
1 [Rugby at George Mason University] *
1 [TEDxGMU] *
1 [Virginia State Route 383]
)
= 1.56
Outbound
1
Tags on post
Inbound
1
Posts tagging this
Connections
9
Total nodes
Base Node Strength
1
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)George Mason University 93.33%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)