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Sankt Polten
Michael Haydn
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Graz
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Linz
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Related Images

Viehofner Seen
Sankt Polten
Sports in Salzburg
Salzburg
Sports in Bregenz
Fountains in St. Pölten
Parks in St. Pölten
Society of Austria
Graz
Traisen River
Objects in Salzburg
Firefighting in Salzburg
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Linz
Bregenz
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Eisenstadt
Klagenfurt, Wulfen-Denkmal
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Innsbruck
Klagenfurt
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Analyzing Network Connections...

Loading Map...

Nearest Locations

  • 📍
    Poland - Croatia, 16 Jun 20080.0 km away
  • 📍
    Haus Hauptplatz 18 in Villach15.1 km away
  • 📍
    Wörthersee37.4 km away
  • 📍
    Klagenfurt am Wörthersee38.6 km away
  • Thumbnail for Klagenfurt
    Klagenfurt38.8 km away

Network Profile

Overall Strength
i
77.88% of network
(23.3K)
Strength Breakdown
  • This Post (77.88%)
  • Michael Haydn (5.77%)
  • Klagenfurt (3.85%)
  • Klagenfurt am Wörthersee (2.88%)
  • Salzburg (1.92%)
  • Österreich (1.92%)
  • Bregenz (0.96%)
  • Eisenstadt (0.96%)
  • Graz (0.96%)
  • Innsbruck (0.96%)
  • Linz (0.96%)
  • Sankt Polten (0.96%)
Influence Score
i
6.67% of network
(4.5)
Influence Breakdown
  • This Post (6.67%)
  • Klagenfurt am Wörthersee (20.00%)
  • Österreich (13.33%)
  • Michael Haydn (10.00%)
  • Bregenz (6.67%)
  • Eisenstadt (6.67%)
  • Graz (6.67%)
  • Innsbruck (6.67%)
  • Klagenfurt (6.67%)
  • Linz (6.67%)
  • Sankt Polten (6.67%)
  • Salzburg (3.33%)
Direct Connections 18

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, 9) = 9
$outbound = max(1, 9) = 9

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 9 * 9 = 81
Base_Influence (IV) = $inbound / $outbound = 9 / 9 = 1

// 3. Exponential Network Values (accumulating 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 81 *
                           ( 3 [Klagenfurt am Wörthersee] *
                            2 [Österreich] *
                            6 [Michael Haydn] *
                            1 [Bregenz] *
                            1 [Eisenstadt] *
                            1 [Graz] *
                            1 [Innsbruck] *
                            4 [Klagenfurt] *
                            1 [Linz] *
                            1 [Sankt Polten] *
                            2 [Salzburg]
                           )

                         = 23.3K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 3 [Klagenfurt am Wörthersee] *
                            2 [Österreich] *
                            1.5 [Michael Haydn] *
                            1 [Bregenz] *
                            1 [Eisenstadt] *
                            1 [Graz] *
                            1 [Innsbruck] *
                            1 [Klagenfurt] *
                            1 [Linz] *
                            1 [Sankt Polten] *
                            0.5 [Salzburg]
                           )

                         = 4.5
Outbound 9 Tags on post
Inbound 9 Posts tagging this
Connections 11 Total nodes
Base Node Strength 81
Base Node Influence 1
Strength Share (vs Direct Neighbours)
77.88% (23.3K overall)
  • This Post (77.88%)
  • Michael Haydn (5.77%)
  • Klagenfurt (3.85%)
  • Klagenfurt am Wörthersee (2.88%)
  • Salzburg (1.92%)
  • Österreich (1.92%)
  • Bregenz (0.96%)
  • Eisenstadt (0.96%)
  • Graz (0.96%)
  • Innsbruck (0.96%)
  • Linz (0.96%)
  • Sankt Polten (0.96%)
Influence Share (vs Direct Neighbours)
6.67% (4.5 overall)
  • This Post (6.67%)
  • Klagenfurt am Wörthersee (20.00%)
  • Österreich (13.33%)
  • Michael Haydn (10.00%)
  • Bregenz (6.67%)
  • Eisenstadt (6.67%)
  • Graz (6.67%)
  • Innsbruck (6.67%)
  • Klagenfurt (6.67%)
  • Linz (6.67%)
  • Sankt Polten (6.67%)
  • Salzburg (3.33%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Klagenfurt am Wörthersee ↗
Str: 3Inf: 3
Österreich ↗
Str: 2Inf: 2
Michael Haydn ↗
Str: 6Inf: 1.5
Bregenz ↗
Str: 1Inf: 1
Eisenstadt ↗
Str: 1Inf: 1
Graz ↗
Str: 1Inf: 1
Innsbruck ↗
Str: 1Inf: 1
Klagenfurt ↗
Str: 4Inf: 1
Linz ↗
Str: 1Inf: 1
Sankt Polten ↗
Str: 1Inf: 1
Salzburg ↗
Str: 2Inf: 0.5
Weakest Connections (Lowest Multipliers)
Salzburg ↗
Str: 2Inf: 0.5
Sankt Polten ↗
Str: 1Inf: 1
Linz ↗
Str: 1Inf: 1
Klagenfurt ↗
Str: 4Inf: 1
Innsbruck ↗
Str: 1Inf: 1
Graz ↗
Str: 1Inf: 1
Eisenstadt ↗
Str: 1Inf: 1
Bregenz ↗
Str: 1Inf: 1
Michael Haydn ↗
Str: 6Inf: 1.5
Österreich ↗
Str: 2Inf: 2
Klagenfurt am Wörthersee ↗
Str: 3Inf: 3

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

Outbound Tags (9)
Österreich
Bregenz
Eisenstadt
Graz
Innsbruck
Klagenfurt
Linz
Salzburg
Sankt Polten
Inbound Posts (9)
Bregenz
Eisenstadt
Graz
Innsbruck
Klagenfurt
Linz
Salzburg
Sankt Polten
Österreich
Last calculated: Jul 24, 4:40 PM
Carinthia, Austria72

Related Content

Composers

  • Michael Haydn

Locations

  • Österreich
  • Klagenfurt am Wörthersee

Regionals

  • Salzburg
  • Sankt Polten
  • Bregenz
  • Eisenstadt
  • Graz
  • Innsbruck
  • Klagenfurt
  • Linz