Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Ludwig van Beethoven
Richard Wagner
Gustav Holst
Don VoorheesChristian Gottlieb MüllerOperas by WagnerKaisermarschMathilde Wesendonck

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 3 days ago
Comments: 0

Eileen Lally
Last login: 3 weeks ago
Comments: 0

Özkan Konu
Last login: 1 month 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: 2 months ago
Comments: 0

Letters about Richard Wagner

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

Related Images

1850
Books written by Richard Wagner
1813
Monuments and memorials to Richard Wagner
Richard-Wagner-Stätten Graupa

Connected Musicians

  • Don Voorhees

Analyzing Network Connections...

Network Profile

Overall Strength
i
0.17% of network
(17.84M)
Strength Breakdown
  • This Post (0.17%)
  • Richard Wagner (10.58%)
  • Gustav Holst (5.95%)
  • Don Voorhees (2.64%)
  • Christian Gottlieb Müller (0.17%)
  • Kaisermarsch (0.17%)
  • Mathilde Wesendonck (0.17%)
  • Operas by Wagner (0.17%)
Dominant nodes (excluded from chart)
Ludwig van Beethoven 80.00%
Influence Score
i
11.11% of network
(1)
Influence Breakdown
  • This Post (11.11%)
  • Richard Wagner (11.11%)
  • Ludwig van Beethoven (11.11%)
  • Gustav Holst (11.11%)
  • Don Voorhees (11.11%)
  • Christian Gottlieb Müller (11.11%)
  • Kaisermarsch (11.11%)
  • Mathilde Wesendonck (11.11%)
  • Operas by Wagner (11.11%)
Direct Connections 2

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

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

// 3. Exponential Network Values (accumulating 8 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 64 [Richard Wagner] *
                            484 [Ludwig van Beethoven] *
                            36 [Gustav Holst] *
                            16 [Don Voorhees] *
                            1 [Christian Gottlieb Müller] *
                            1 [Kaisermarsch] *
                            1 [Mathilde Wesendonck] *
                            1 [Operas by Wagner]
                           )

                         = 17.84M

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Richard Wagner] *
                            1 [Ludwig van Beethoven] *
                            1 [Gustav Holst] *
                            1 [Don Voorhees] *
                            1 [Christian Gottlieb Müller] *
                            1 [Kaisermarsch] *
                            1 [Mathilde Wesendonck] *
                            1 [Operas by Wagner]
                           )

                         = 1
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 8 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.17% (17.84M overall)
  • This Post (0.17%)
  • Richard Wagner (10.58%)
  • Gustav Holst (5.95%)
  • Don Voorhees (2.64%)
  • Christian Gottlieb Müller (0.17%)
  • Kaisermarsch (0.17%)
  • Mathilde Wesendonck (0.17%)
  • Operas by Wagner (0.17%)
Dominant nodes (excluded from chart)
Ludwig van Beethoven 80.00%
Influence Share (vs Direct Neighbours)
11.11% (1 overall)
  • This Post (11.11%)
  • Richard Wagner (11.11%)
  • Ludwig van Beethoven (11.11%)
  • Gustav Holst (11.11%)
  • Don Voorhees (11.11%)
  • Christian Gottlieb Müller (11.11%)
  • Kaisermarsch (11.11%)
  • Mathilde Wesendonck (11.11%)
  • Operas by Wagner (11.11%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Richard Wagner ↗
Str: 64Inf: 1
Ludwig van Beethoven ↗
Str: 484Inf: 1
Gustav Holst ↗
Str: 36Inf: 1
Don Voorhees ↗
Str: 16Inf: 1
Christian Gottlieb Müller ↗
Str: 1Inf: 1
Kaisermarsch ↗
Str: 1Inf: 1
Mathilde Wesendonck ↗
Str: 1Inf: 1
Operas by Wagner ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Operas by Wagner ↗
Str: 1Inf: 1
Mathilde Wesendonck ↗
Str: 1Inf: 1
Kaisermarsch ↗
Str: 1Inf: 1
Christian Gottlieb Müller ↗
Str: 1Inf: 1
Don Voorhees ↗
Str: 16Inf: 1
Gustav Holst ↗
Str: 36Inf: 1
Ludwig van Beethoven ↗
Str: 484Inf: 1
Richard Wagner ↗
Str: 64Inf: 1

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

Outbound Tags (1)
Richard Wagner
Inbound Posts (1)
Richard Wagner
Last calculated: Jun 26, 5:54 AM
34

Related Content

Composers

  • Operas by Wagner
  • Richard Wagner
  • Ludwig van Beethoven
  • Gustav Holst
  • Christian Gottlieb Müller
  • Kaisermarsch
  • Mathilde Wesendonck