Network Profile
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Influence Score
31.58%
of network
Direct Connections
4
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 2 direct neighbours)
Network Strength (CV) = Node PV × (Π Neighbour PVs) =
144
Network Influence (TV) = Node IV × (Π Neighbour IVs) =
1.00005
Outbound
2
Tags on post
Inbound
2
Posts tagging this
Base Node Strength
4
Base Node Influence
1
Connected Nodes
2
Strength Share (vs Direct Neighbours)
This Post (25.00%) Jacob Israel de Haan (37.50%) Jacob Israël de Haanstraat, Amsterdam (37.50%)
Influence Share (vs Direct Neighbours)
This Post (31.58%) Jacob Israel de Haan (47.37%) Jacob Israël de Haanstraat, Amsterdam (21.05%)
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, 2:58 AM
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Amsterdam, North Holland, Netherlands
👁️ 9 Views