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Frederiksberg
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Related Images

Frederiksberg
Flintholm
Peter Bangs Vej Station
Frederiksberg Kirke
Royal Copenhagen porcelain

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Copenhagen Business School
    Copenhagen Business School0.4 km away
  • Thumbnail for Frederiksberg
    Frederiksberg0.8 km away
  • Thumbnail for Frederiksberg Kirke
    Frederiksberg Kirke0.9 km away
  • 📍
    Cisternerne1.1 km away
  • Thumbnail for Peter Bangs Vej Station
    Peter Bangs Vej Station1.3 km away

Network Profile

Overall Strength
i
21.43% of network
(5.8K)
Strength Breakdown
  • This Post (21.43%)
  • Royal Copenhagen (47.62%)
  • Frederiksberg (19.05%)
  • Philip Julius Schou (9.52%)
  • Bing & Grøndahl (2.38%)
Influence Score
i
16.00% of network
(2.5)
Influence Breakdown
  • This Post (16.00%)
  • Frederiksberg (32.00%)
  • Royal Copenhagen (20.00%)
  • Philip Julius Schou (16.00%)
  • Bing & Grøndahl (16.00%)
Direct Connections 6

Node & Network Details

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, 3) = 3
$outbound = max(1, 3) = 3

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 3 * 3 = 9
Base_Influence (IV) = $inbound / $outbound = 3 / 3 = 1

// 3. Exponential Network Values (accumulating 4 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 9 *
                           ( 8 [Frederiksberg] *
                            20 [Royal Copenhagen] *
                            4 [Philip Julius Schou] *
                            1 [Bing & Grøndahl]
                           )

                         = 5.8K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 2 [Frederiksberg] *
                            1.25 [Royal Copenhagen] *
                            1 [Philip Julius Schou] *
                            1 [Bing & Grøndahl]
                           )

                         = 2.5
Outbound 3 Tags on post
Inbound 3 Posts tagging this
Connections 4 Total nodes
Base Node Strength 9
Base Node Influence 1
Strength Share (vs Direct Neighbours)
21.43% (5.8K overall)
  • This Post (21.43%)
  • Royal Copenhagen (47.62%)
  • Frederiksberg (19.05%)
  • Philip Julius Schou (9.52%)
  • Bing & Grøndahl (2.38%)
Influence Share (vs Direct Neighbours)
16.00% (2.5 overall)
  • This Post (16.00%)
  • Frederiksberg (32.00%)
  • Royal Copenhagen (20.00%)
  • Philip Julius Schou (16.00%)
  • Bing & Grøndahl (16.00%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Frederiksberg ↗
Str: 8Inf: 2
Royal Copenhagen ↗
Str: 20Inf: 1.25
Philip Julius Schou ↗
Str: 4Inf: 1
Bing & Grøndahl ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Bing & Grøndahl ↗
Str: 1Inf: 1
Philip Julius Schou ↗
Str: 4Inf: 1
Royal Copenhagen ↗
Str: 20Inf: 1.25
Frederiksberg ↗
Str: 8Inf: 2

Connection Health Audit (Red = broken 1-way link)

Outbound Tags (3)
Frederiksberg
Philip Julius Schou
Royal Copenhagen
Inbound Posts (3)
Frederiksberg
Royal Copenhagen
Philip Julius Schou
Last calculated: Jun 11, 5:21 AM
Capital Region of Denmark, Denmark25

Related Content

Figures

  • Philip Julius Schou

Locations

  • Royal Copenhagen

Regionals

  • Frederiksberg

Topics

  • Bing & Grøndahl