Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Trains at Hillerød StationBuses at Hillerød StationHolte Station1st central station of HelsingørHellerup StationKlampenborg Station
Vilhelm Carl Heinrich Wolf

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 3 days ago
Comments: 0

Eileen Lally
Last login: 2 weeks ago
Comments: 0

Özkan Konu
Last login: 4 weeks ago
Comments: 0

Anne Marie Bevan
Last login: 1 month ago
Comments: 0

Kevin Greene
Last login: 1 month ago
Comments: 0

Seán Millar
Last login: 1 month ago
Comments: 0

Hillerød Station

Loading Graph...
Press Spacebar to toggle layout
Join the conversation

💬 Know something?

Sign in to leave a note, add a photo, or make a connection.

Continue with Google Continue with Facebook

Keep Muso free

Muso is built by one person, for the love of it. no investors — just your support.

€10
Covers an hour of research
Most popular
€25
Keeps the archive running
€50
Funds a full week of work
✎ Enter my own amount
€5
per month · cancel any time

You'll confirm the amount on the next screen

Donate €25 →
Secure checkout via Stripe  ·  No account needed

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • 📍
    Amager7.3 km away
  • 📍
    Copenhagen history7.3 km away
  • 📍
    North Coast14.9 km away
  • 📍
    Aggebo Hegn16.1 km away
  • 📍
    Holte Station16.5 km away

Network Profile

Overall Strength
i
19.57% of network
(3.6K)
Strength Breakdown
  • This Post (19.57%)
  • Hellerup Station (8.70%)
  • Klampenborg Station (8.70%)
  • 1st central station of Helsingør (2.17%)
  • Holte Station (2.17%)
  • Buses at Hillerød Station (2.17%)
  • Trains at Hillerød Station (2.17%)
Dominant nodes (excluded from chart)
Vilhelm Carl Heinrich Wolf 54.35%
Influence Score
i
12.50% of network
(1)
Influence Breakdown
  • This Post (12.50%)
  • Vilhelm Carl Heinrich Wolf (12.50%)
  • 1st central station of Helsingør (12.50%)
  • Hellerup Station (12.50%)
  • Holte Station (12.50%)
  • Klampenborg Station (12.50%)
  • Buses at Hillerød Station (12.50%)
  • Trains at Hillerød Station (12.50%)
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 7 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 9 *
                           ( 25 [Vilhelm Carl Heinrich Wolf] *
                            1 [1st central station of Helsingør] *
                            4 [Hellerup Station] *
                            1 [Holte Station] *
                            4 [Klampenborg Station] *
                            1 [Buses at Hillerød Station] *
                            1 [Trains at Hillerød Station]
                           )

                         = 3.6K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Vilhelm Carl Heinrich Wolf] *
                            1 [1st central station of Helsingør] *
                            1 [Hellerup Station] *
                            1 [Holte Station] *
                            1 [Klampenborg Station] *
                            1 [Buses at Hillerød Station] *
                            1 [Trains at Hillerød Station]
                           )

                         = 1
Outbound 3 Tags on post
Inbound 3 Posts tagging this
Connections 7 Total nodes
Base Node Strength 9
Base Node Influence 1
Strength Share (vs Direct Neighbours)
19.57% (3.6K overall)
  • This Post (19.57%)
  • Hellerup Station (8.70%)
  • Klampenborg Station (8.70%)
  • 1st central station of Helsingør (2.17%)
  • Holte Station (2.17%)
  • Buses at Hillerød Station (2.17%)
  • Trains at Hillerød Station (2.17%)
Dominant nodes (excluded from chart)
Vilhelm Carl Heinrich Wolf 54.35%
Influence Share (vs Direct Neighbours)
12.50% (1 overall)
  • This Post (12.50%)
  • Vilhelm Carl Heinrich Wolf (12.50%)
  • 1st central station of Helsingør (12.50%)
  • Hellerup Station (12.50%)
  • Holte Station (12.50%)
  • Klampenborg Station (12.50%)
  • Buses at Hillerød Station (12.50%)
  • Trains at Hillerød Station (12.50%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Vilhelm Carl Heinrich Wolf ↗
Str: 25Inf: 1
1st central station of Helsingør ↗
Str: 1Inf: 1
Hellerup Station ↗
Str: 4Inf: 1
Holte Station ↗
Str: 1Inf: 1
Klampenborg Station ↗
Str: 4Inf: 1
Buses at Hillerød Station ↗
Str: 1Inf: 1
Trains at Hillerød Station ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Trains at Hillerød Station ↗
Str: 1Inf: 1
Buses at Hillerød Station ↗
Str: 1Inf: 1
Klampenborg Station ↗
Str: 4Inf: 1
Holte Station ↗
Str: 1Inf: 1
Hellerup Station ↗
Str: 4Inf: 1
1st central station of Helsingør ↗
Str: 1Inf: 1
Vilhelm Carl Heinrich Wolf ↗
Str: 25Inf: 1

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

Outbound Tags (3)
Buses at Hillerød Station
Trains at Hillerød Station
Vilhelm Carl Heinrich Wolf
Inbound Posts (3)
Vilhelm Carl Heinrich Wolf
Buses at Hillerød Station
Trains at Hillerød Station
Last calculated: Jun 18, 5:55 PM
Capital Region of Denmark, Denmark7

Related Content

Figures

  • Vilhelm Carl Heinrich Wolf

Topics

  • Hellerup Station
  • Holte Station
  • Klampenborg Station
  • Buses at Hillerød Station
  • Trains at Hillerød Station
  • 1st central station of Helsingør