Network Profile
Node & Network Strength Details
How is this calculated? The math continuously tracks how strongly this post is connected to the rest of the website.
Every tag forms a network link. The pie charts below show each connected post's base strength (PV) and influence (IV) as a share of this post's direct neighbourhood.
// 1. Base variables (minimum value of 1 to prevent zero-multiplication issues)
Outbound ($in) = max(1, 2) =
2
Inbound ($out) = max(1, 1) =
1
// 2. Node Base Values
Base Strength (PV) = $in × $out = 2 × 1 =
2
Base Influence (IV) = $in ÷ $out = 2 ÷ 1 =
2
// 3. Network Exponential Values (accumulating 3 direct neighbours)
Network Strength (CV) = Node PV × (Π Neighbour PVs) =
16
Network Influence (TV) = Node IV × (Π Neighbour IVs) =
16
Outbound
2
Tags on post
Inbound
1
Posts tagging this
Base Node Strength
2
Base Node Influence
2
Connected Nodes
3
Strength Share (vs Direct Neighbours)
- This Post (25.00%)
- Coliseum cinema Ekaterinburg (25.00%)
- Yekaterinburg Dom Kino (25.00%)
- Baumana Street 2, Yekaterinburg (25.00%)
Influence Share (vs Direct Neighbours)
- This Post (25.00%)
- Coliseum cinema Ekaterinburg (25.00%)
- Yekaterinburg Dom Kino (25.00%)
- Baumana Street 2, Yekaterinburg (25.00%)
Connected Network (How neighbours affect this node)
Top Network Boosters (Highest Multipliers)
Weakest Connections (Lowest Multipliers)
Connection Health Audit (Red = broken 1-way link)
Last calculated math cycle: May 5, 3:08 AM
Analyzing Network Connections...
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Nearest Locations
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Yekaterinburg, Yekaterinburg Municipality, Russia
👁️ 5 Views