Analyzing Network Connections...
Network Profile
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, 9) = 9
$outbound = max(1, 9) = 9
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 9 * 9 = 81
Base_Influence (IV) = $inbound / $outbound = 9 / 9 = 1
// 3. Exponential Network Values (accumulating 15 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 81 *
( 1 [Nena] *
1 [Nenad Gajin] *
1 [Vlada Samardžić] *
1 [Srđan Dunkić] *
1 [Predrag Milutinović] *
1 [Miroslav Tovirac] *
1 [Igor Malešević] *
1 [Branko Trijić] *
49 [Bojan Ivković] *
1 [Havana Whisper] *
1 [Kontrabanda] *
1 [Pavle Aksentijević I Grupa Zapis] *
1 [Hush (14)] *
1 [Vrooom] *
1 [Sanja Ilić & Balkanika]
)
= 4K
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1 [Nena] *
1 [Nenad Gajin] *
1 [Vlada Samardžić] *
1 [Srđan Dunkić] *
1 [Predrag Milutinović] *
1 [Miroslav Tovirac] *
1 [Igor Malešević] *
1 [Branko Trijić] *
1 [Bojan Ivković] *
1 [Havana Whisper] *
1 [Kontrabanda] *
1 [Pavle Aksentijević I Grupa Zapis] *
1 [Hush (14)] *
1 [Vrooom] *
1 [Sanja Ilić & Balkanika]
)
= 1
Outbound
9
Tags on post
Inbound
9
Posts tagging this
Connections
15
Total nodes
Base Node Strength
81
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Bojan Ivković 34.03%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)
Last calculated: Jun 16, 7:38 AM
Belgrade, City of Belgrade, Serbia
23
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