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Markus SiegenhortFelix WylezikCedric HollerFlorian DammaschJulian WulfheideTom Innocenti

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Connected Musicians

  • Cedric Holler
  • Felix Wylezik
  • Florian Dammasch
  • Julian Wulfheide
  • Markus Siegenhort
  • Tom Innocenti

Analyzing Network Connections...

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Nearest Locations

  • 📍
    xXx: State of the Union0.0 km away
  • Thumbnail for Avengers: Age of Ultron
    Avengers: Age of Ultron0.0 km away
  • 📍
    Captain America: Civil War0.0 km away
  • Thumbnail for Ice Cube
    Ice Cube0.0 km away
  • Thumbnail for MOSTLY AUTUMN
    MOSTLY AUTUMN0.0 km away

Network Profile

Overall Strength
i
85.71% of network
(36)
Strength Breakdown
  • This Post (85.71%)
  • Markus Siegenhort (2.38%)
  • Cedric Holler (2.38%)
  • Felix Wylezik (2.38%)
  • Florian Dammasch (2.38%)
  • Julian Wulfheide (2.38%)
  • Tom Innocenti (2.38%)
Influence Score
i
14.29% of network
(1)
Influence Breakdown
  • This Post (14.29%)
  • Markus Siegenhort (14.29%)
  • Cedric Holler (14.29%)
  • Felix Wylezik (14.29%)
  • Florian Dammasch (14.29%)
  • Julian Wulfheide (14.29%)
  • Tom Innocenti (14.29%)
Direct Connections 12

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, 6) = 6
$outbound = max(1, 6) = 6

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 6 * 6 = 36
Base_Influence (IV) = $inbound / $outbound = 6 / 6 = 1

// 3. Exponential Network Values (accumulating 6 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 36 *
                           ( 1 [Markus Siegenhort] *
                            1 [Cedric Holler] *
                            1 [Felix Wylezik] *
                            1 [Florian Dammasch] *
                            1 [Julian Wulfheide] *
                            1 [Tom Innocenti]
                           )

                         = 36

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Markus Siegenhort] *
                            1 [Cedric Holler] *
                            1 [Felix Wylezik] *
                            1 [Florian Dammasch] *
                            1 [Julian Wulfheide] *
                            1 [Tom Innocenti]
                           )

                         = 1
Outbound 6 Tags on post
Inbound 6 Posts tagging this
Connections 6 Total nodes
Base Node Strength 36
Base Node Influence 1
Strength Share (vs Direct Neighbours)
85.71% (36 overall)
  • This Post (85.71%)
  • Markus Siegenhort (2.38%)
  • Cedric Holler (2.38%)
  • Felix Wylezik (2.38%)
  • Florian Dammasch (2.38%)
  • Julian Wulfheide (2.38%)
  • Tom Innocenti (2.38%)
Influence Share (vs Direct Neighbours)
14.29% (1 overall)
  • This Post (14.29%)
  • Markus Siegenhort (14.29%)
  • Cedric Holler (14.29%)
  • Felix Wylezik (14.29%)
  • Florian Dammasch (14.29%)
  • Julian Wulfheide (14.29%)
  • Tom Innocenti (14.29%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Markus Siegenhort ↗
Str: 1Inf: 1
Cedric Holler ↗
Str: 1Inf: 1
Felix Wylezik ↗
Str: 1Inf: 1
Florian Dammasch ↗
Str: 1Inf: 1
Julian Wulfheide ↗
Str: 1Inf: 1
Tom Innocenti ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Tom Innocenti ↗
Str: 1Inf: 1
Julian Wulfheide ↗
Str: 1Inf: 1
Florian Dammasch ↗
Str: 1Inf: 1
Felix Wylezik ↗
Str: 1Inf: 1
Cedric Holler ↗
Str: 1Inf: 1
Markus Siegenhort ↗
Str: 1Inf: 1

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

Outbound Tags (6)
Cedric Holler
Felix Wylezik
Florian Dammasch
Julian Wulfheide
Markus Siegenhort
Tom Innocenti
Inbound Posts (6)
Markus Siegenhort
Cedric Holler
Felix Wylezik
Florian Dammasch
Julian Wulfheide
Tom Innocenti
Last calculated: Jun 11, 9:56 AM
Avery County, United States29

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