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 ($in) = max(1, 5) =
5
Inbound ($out) = max(1, 2) =
2
// 2. Node Base Values
Base Strength (PV) = $in × $out = 5 × 2 =
10
Base Influence (IV) = $in ÷ $out = 5 ÷ 2 =
2.5
// 3. Network Exponential Values (accumulating 3 direct neighbours)
Network Strength (CV) = Node PV × (Π Neighbour PVs) =
160
Network Influence (TV) = Node IV × (Π Neighbour IVs) =
10
Outbound
5
Tags on post
Inbound
2
Posts tagging this
Base Node Strength
10
Base Node Influence
2.5
Connected Nodes
3
Strength Share (vs Direct Neighbours)
- This Post (55.56%)
- Roter Matrose (22.22%)
- Hans-Jürgen Graf von Blumenthal (11.11%)
- ZIEL ERKANNT! 12. Reichs-Frontsoldatentag des Stahlhelm B.d.F. Breslau 30 31 Mai 1931 (11.11%)
Influence Share (vs Direct Neighbours)
- This Post (33.33%)
- Hans-Jürgen Graf von Blumenthal (26.67%)
- ZIEL ERKANNT! 12. Reichs-Frontsoldatentag des Stahlhelm B.d.F. Breslau 30 31 Mai 1931 (26.67%)
- Roter Matrose (13.33%)
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, 6:22 AM
Analyzing Network Connections...
Bavaria, Germany
👁️ 18 Views