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Second Viennese School
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Connected Musicians

  • Egon Wellesz
    Egon Wellesz band photo
  • Rudolf Kolisch

Analyzing Network Connections...

Network Profile

Overall Strength
i
0.48% of network
(1.33 × 1018)
Strength Breakdown
  • This Post (0.48%)
  • Alexander Zemlinskey 1871 (1.08%)
  • Rudolf Kolisch (1.08%)
  • Vienna Conservatory (0.48%)
  • Giacinto Scelsi (0.48%)
  • Alexander von Zemlinsky (0.48%)
  • Nikos Skalkottas (0.48%)
  • Hanns Eisler (0.48%)
  • Leon Kirchner (0.12%)
  • Stefania Turkewich (0.12%)
  • Oscar Levant (0.12%)
  • Egon Wellesz (0.12%)
  • Earl Kim (0.12%)
  • Dika Newlin (0.12%)
  • Charles Rosen (0.12%)
  • Ernst Krenek (0.12%)
  • alan berg (0.12%)
  • Viktor Ullmann (0.12%)
  • Erwin Stein (0.12%)
  • Alexander Zemlinsky (0.12%)
  • Viennese trichords (0.12%)
  • Karl Rankl (0.12%)
Dominant nodes (excluded from chart)
Arnold Schoenberg 43.29%Second Viennese School 28.78%Anton Webern 5.88%UCLA 5.04%Alban Berg 4.32%Lars Erik Larsson 3.00%Theodor W. Adorno 3.00%
Influence Score
i
3.42% of network
(1.24)
Influence Breakdown
  • This Post (3.42%)
  • UCLA (3.99%)
  • Second Viennese School (3.65%)
  • Alexander Zemlinskey 1871 (3.42%)
  • Vienna Conservatory (3.42%)
  • Lars Erik Larsson (3.42%)
  • Leon Kirchner (3.42%)
  • Giacinto Scelsi (3.42%)
  • Alexander von Zemlinsky (3.42%)
  • Alban Berg (3.42%)
  • Arnold Schoenberg (3.42%)
  • Nikos Skalkottas (3.42%)
  • Hanns Eisler (3.42%)
  • Theodor W. Adorno (3.42%)
  • Stefania Turkewich (3.42%)
  • Oscar Levant (3.42%)
  • Egon Wellesz (3.42%)
  • Earl Kim (3.42%)
  • Dika Newlin (3.42%)
  • Charles Rosen (3.42%)
  • Ernst Krenek (3.42%)
  • Anton Webern (3.42%)
  • alan berg (3.42%)
  • Viktor Ullmann (3.42%)
  • Rudolf Kolisch (3.42%)
  • Erwin Stein (3.42%)
  • Alexander Zemlinsky (3.42%)
  • Viennese trichords (3.42%)
  • Karl Rankl (3.42%)
Direct Connections 4

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, 2) = 2
$outbound = max(1, 2) = 2

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 2 * 2 = 4
Base_Influence (IV) = $inbound / $outbound = 2 / 2 = 1

// 3. Exponential Network Values (accumulating 28 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 4 *
                           ( 42 [UCLA] *
                            240 [Second Viennese School] *
                            9 [Alexander Zemlinskey 1871] *
                            4 [Vienna Conservatory] *
                            25 [Lars Erik Larsson] *
                            1 [Leon Kirchner] *
                            4 [Giacinto Scelsi] *
                            4 [Alexander von Zemlinsky] *
                            36 [Alban Berg] *
                            361 [Arnold Schoenberg] *
                            4 [Nikos Skalkottas] *
                            4 [Hanns Eisler] *
                            25 [Theodor W. Adorno] *
                            1 [Stefania Turkewich] *
                            1 [Oscar Levant] *
                            1 [Egon Wellesz] *
                            1 [Earl Kim] *
                            1 [Dika Newlin] *
                            1 [Charles Rosen] *
                            1 [Ernst Krenek] *
                            49 [Anton Webern] *
                            1 [alan berg] *
                            1 [Viktor Ullmann] *
                            9 [Rudolf Kolisch] *
                            1 [Erwin Stein] *
                            1 [Alexander Zemlinsky] *
                            1 [Viennese trichords] *
                            1 [Karl Rankl]
                           )

                         = 1.33 x 10^18

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1.17 [UCLA] *
                            1.07 [Second Viennese School] *
                            1 [Alexander Zemlinskey 1871] *
                            1 [Vienna Conservatory] *
                            1 [Lars Erik Larsson] *
                            1 [Leon Kirchner] *
                            1 [Giacinto Scelsi] *
                            1 [Alexander von Zemlinsky] *
                            1 [Alban Berg] *
                            1 [Arnold Schoenberg] *
                            1 [Nikos Skalkottas] *
                            1 [Hanns Eisler] *
                            1 [Theodor W. Adorno] *
                            1 [Stefania Turkewich] *
                            1 [Oscar Levant] *
                            1 [Egon Wellesz] *
                            1 [Earl Kim] *
                            1 [Dika Newlin] *
                            1 [Charles Rosen] *
                            1 [Ernst Krenek] *
                            1 [Anton Webern] *
                            1 [alan berg] *
                            1 [Viktor Ullmann] *
                            1 [Rudolf Kolisch] *
                            1 [Erwin Stein] *
                            1 [Alexander Zemlinsky] *
                            1 [Viennese trichords] *
                            1 [Karl Rankl]
                           )

                         = 1.24
Outbound 2 Tags on post
Inbound 2 Posts tagging this
Connections 28 Total nodes
Base Node Strength 4
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.48% (1.33 × 1018 overall)
  • This Post (0.48%)
  • Alexander Zemlinskey 1871 (1.08%)
  • Rudolf Kolisch (1.08%)
  • Vienna Conservatory (0.48%)
  • Giacinto Scelsi (0.48%)
  • Alexander von Zemlinsky (0.48%)
  • Nikos Skalkottas (0.48%)
  • Hanns Eisler (0.48%)
  • Leon Kirchner (0.12%)
  • Stefania Turkewich (0.12%)
  • Oscar Levant (0.12%)
  • Egon Wellesz (0.12%)
  • Earl Kim (0.12%)
  • Dika Newlin (0.12%)
  • Charles Rosen (0.12%)
  • Ernst Krenek (0.12%)
  • alan berg (0.12%)
  • Viktor Ullmann (0.12%)
  • Erwin Stein (0.12%)
  • Alexander Zemlinsky (0.12%)
  • Viennese trichords (0.12%)
  • Karl Rankl (0.12%)
Dominant nodes (excluded from chart)
Arnold Schoenberg 43.29%Second Viennese School 28.78%Anton Webern 5.88%UCLA 5.04%Alban Berg 4.32%Lars Erik Larsson 3.00%Theodor W. Adorno 3.00%
Influence Share (vs Direct Neighbours)
3.42% (1.24 overall)
  • This Post (3.42%)
  • UCLA (3.99%)
  • Second Viennese School (3.65%)
  • Alexander Zemlinskey 1871 (3.42%)
  • Vienna Conservatory (3.42%)
  • Lars Erik Larsson (3.42%)
  • Leon Kirchner (3.42%)
  • Giacinto Scelsi (3.42%)
  • Alexander von Zemlinsky (3.42%)
  • Alban Berg (3.42%)
  • Arnold Schoenberg (3.42%)
  • Nikos Skalkottas (3.42%)
  • Hanns Eisler (3.42%)
  • Theodor W. Adorno (3.42%)
  • Stefania Turkewich (3.42%)
  • Oscar Levant (3.42%)
  • Egon Wellesz (3.42%)
  • Earl Kim (3.42%)
  • Dika Newlin (3.42%)
  • Charles Rosen (3.42%)
  • Ernst Krenek (3.42%)
  • Anton Webern (3.42%)
  • alan berg (3.42%)
  • Viktor Ullmann (3.42%)
  • Rudolf Kolisch (3.42%)
  • Erwin Stein (3.42%)
  • Alexander Zemlinsky (3.42%)
  • Viennese trichords (3.42%)
  • Karl Rankl (3.42%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
UCLA ↗
Str: 42Inf: 1.17
Second Viennese School ↗
Str: 240Inf: 1.07
Alexander Zemlinskey 1871 ↗
Str: 9Inf: 1
Vienna Conservatory ↗
Str: 4Inf: 1
Lars Erik Larsson ↗
Str: 25Inf: 1
Leon Kirchner ↗
Str: 1Inf: 1
Giacinto Scelsi ↗
Str: 4Inf: 1
Alexander von Zemlinsky ↗
Str: 4Inf: 1
Alban Berg ↗
Str: 36Inf: 1
Arnold Schoenberg ↗
Str: 361Inf: 1
Nikos Skalkottas ↗
Str: 4Inf: 1
Hanns Eisler ↗
Str: 4Inf: 1
Theodor W. Adorno ↗
Str: 25Inf: 1
Stefania Turkewich ↗
Str: 1Inf: 1
Oscar Levant ↗
Str: 1Inf: 1
Egon Wellesz ↗
Str: 1Inf: 1
Earl Kim ↗
Str: 1Inf: 1
Dika Newlin ↗
Str: 1Inf: 1
Charles Rosen ↗
Str: 1Inf: 1
Ernst Krenek ↗
Str: 1Inf: 1
Anton Webern ↗
Str: 49Inf: 1
alan berg ↗
Str: 1Inf: 1
Viktor Ullmann ↗
Str: 1Inf: 1
Rudolf Kolisch ↗
Str: 9Inf: 1
Erwin Stein ↗
Str: 1Inf: 1
Alexander Zemlinsky ↗
Str: 1Inf: 1
Viennese trichords ↗
Str: 1Inf: 1
Karl Rankl ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Karl Rankl ↗
Str: 1Inf: 1
Viennese trichords ↗
Str: 1Inf: 1
Alexander Zemlinsky ↗
Str: 1Inf: 1
Erwin Stein ↗
Str: 1Inf: 1
Rudolf Kolisch ↗
Str: 9Inf: 1
Viktor Ullmann ↗
Str: 1Inf: 1
alan berg ↗
Str: 1Inf: 1
Anton Webern ↗
Str: 49Inf: 1
Ernst Krenek ↗
Str: 1Inf: 1
Charles Rosen ↗
Str: 1Inf: 1
Dika Newlin ↗
Str: 1Inf: 1
Earl Kim ↗
Str: 1Inf: 1
Egon Wellesz ↗
Str: 1Inf: 1
Oscar Levant ↗
Str: 1Inf: 1
Stefania Turkewich ↗
Str: 1Inf: 1
Theodor W. Adorno ↗
Str: 25Inf: 1
Hanns Eisler ↗
Str: 4Inf: 1
Nikos Skalkottas ↗
Str: 4Inf: 1
Arnold Schoenberg ↗
Str: 361Inf: 1
Alban Berg ↗
Str: 36Inf: 1
Alexander von Zemlinsky ↗
Str: 4Inf: 1
Giacinto Scelsi ↗
Str: 4Inf: 1
Leon Kirchner ↗
Str: 1Inf: 1
Lars Erik Larsson ↗
Str: 25Inf: 1
Vienna Conservatory ↗
Str: 4Inf: 1
Alexander Zemlinskey 1871 ↗
Str: 9Inf: 1
Second Viennese School ↗
Str: 240Inf: 1.07
UCLA ↗
Str: 42Inf: 1.17

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

Outbound Tags (2)
Arnold Schoenberg
second viennese school
Inbound Posts (2)
Arnold Schoenberg
Second Viennese School
Last calculated: Aug 31, 2:07 PM
71

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Composers

  • Arnold Schoenberg
  • Dika Newlin
  • Alexander Zemlinskey 1871
  • Charles Rosen
  • Karl Rankl
  • Nikos Skalkottas
  • Ernst Krenek
  • Lars Erik Larsson
  • Hanns Eisler
  • Anton Webern
  • Leon Kirchner
  • Theodor W. Adorno
  • alan berg
  • Giacinto Scelsi
  • Stefania Turkewich
  • Viktor Ullmann
  • Alexander von Zemlinsky
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Educations

  • UCLA
  • Second Viennese School
  • Vienna Conservatory

Topics

  • Viennese trichords