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Paddy Holgate
Young Shadows
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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, 2) =
2
// 2. Node Base Values
Base Strength (PV) = $in × $out = 2 × 2 =
4
Base Influence (IV) = $in ÷ $out = 2 ÷ 2 =
1
// 3. Network Exponential Values (accumulating 8 direct neighbours)
Network Strength (CV) = Node PV × (Π Neighbour PVs) =
84.93M
Network Influence (TV) = Node IV × (Π Neighbour IVs) =
1
Outbound
2
Tags on post
Inbound
2
Posts tagging this
Base Node Strength
4
Base Node Influence
1
Connected Nodes
8
Strength Share (vs Direct Neighbours)
- This Post (2.92%)
- Tommy Walsh (11.68%)
- Jimmy O'Neill (11.68%)
- pat long (2.92%)
- Liam Compelli (2.92%)
- John J. Scanlon (2.92%)
- Jimmy Storey (2.92%)
- eamonn pollard (2.92%)
Dominant nodes (excluded from chart)Young Shadows 59.12%
Influence Share (vs Direct Neighbours)
- This Post (11.11%)
- Tommy Walsh (11.11%)
- Jimmy O'Neill (11.11%)
- Young Shadows (11.11%)
- pat long (11.11%)
- Liam Compelli (11.11%)
- John J. Scanlon (11.11%)
- Jimmy Storey (11.11%)
- eamonn pollard (11.11%)
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, 6:08 AM
Analyzing Network Connections...
👁️ 30 Views
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