Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Todd Hansen (2)Alan McFarlandDan FoordMan Must DieJohn Lee (23)James Burke (6)Renne HauffeJoe McGlynn

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 2 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

Daniel Firth (2)

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

Connected Bands/Artists

  • Man Must Die

Connected Musicians

  • Alan McFarland
  • Dan Foord
  • James Burke (6)
  • Joe McGlynn
  • John Lee (23)
  • Renne Hauffe
  • Todd Hansen (2)

Analyzing Network Connections...

Network Profile

Overall Strength
i
1.14% of network
(5.2K)
Strength Breakdown
  • This Post (1.14%)
  • Dan Foord (10.23%)
  • Todd Hansen (2) (10.23%)
  • Alan McFarland (1.14%)
  • Joe McGlynn (1.14%)
  • Renne Hauffe (1.14%)
  • James Burke (6) (1.14%)
  • John Lee (23) (1.14%)
Dominant nodes (excluded from chart)
Man Must Die 72.73%
Influence Score
i
11.11% of network
(1)
Influence Breakdown
  • This Post (11.11%)
  • Dan Foord (11.11%)
  • Man Must Die (11.11%)
  • Alan McFarland (11.11%)
  • Joe McGlynn (11.11%)
  • Renne Hauffe (11.11%)
  • Todd Hansen (2) (11.11%)
  • James Burke (6) (11.11%)
  • John Lee (23) (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 *
                           ( 9 [Dan Foord] *
                            64 [Man Must Die] *
                            1 [Alan McFarland] *
                            1 [Joe McGlynn] *
                            1 [Renne Hauffe] *
                            9 [Todd Hansen (2)] *
                            1 [James Burke (6)] *
                            1 [John Lee (23)]
                           )

                         = 5.2K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Dan Foord] *
                            1 [Man Must Die] *
                            1 [Alan McFarland] *
                            1 [Joe McGlynn] *
                            1 [Renne Hauffe] *
                            1 [Todd Hansen (2)] *
                            1 [James Burke (6)] *
                            1 [John Lee (23)]
                           )

                         = 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)
1.14% (5.2K overall)
  • This Post (1.14%)
  • Dan Foord (10.23%)
  • Todd Hansen (2) (10.23%)
  • Alan McFarland (1.14%)
  • Joe McGlynn (1.14%)
  • Renne Hauffe (1.14%)
  • James Burke (6) (1.14%)
  • John Lee (23) (1.14%)
Dominant nodes (excluded from chart)
Man Must Die 72.73%
Influence Share (vs Direct Neighbours)
11.11% (1 overall)
  • This Post (11.11%)
  • Dan Foord (11.11%)
  • Man Must Die (11.11%)
  • Alan McFarland (11.11%)
  • Joe McGlynn (11.11%)
  • Renne Hauffe (11.11%)
  • Todd Hansen (2) (11.11%)
  • James Burke (6) (11.11%)
  • John Lee (23) (11.11%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Dan Foord ↗
Str: 9Inf: 1
Man Must Die ↗
Str: 64Inf: 1
Alan McFarland ↗
Str: 1Inf: 1
Joe McGlynn ↗
Str: 1Inf: 1
Renne Hauffe ↗
Str: 1Inf: 1
Todd Hansen (2) ↗
Str: 9Inf: 1
James Burke (6) ↗
Str: 1Inf: 1
John Lee (23) ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
John Lee (23) ↗
Str: 1Inf: 1
James Burke (6) ↗
Str: 1Inf: 1
Todd Hansen (2) ↗
Str: 9Inf: 1
Renne Hauffe ↗
Str: 1Inf: 1
Joe McGlynn ↗
Str: 1Inf: 1
Alan McFarland ↗
Str: 1Inf: 1
Man Must Die ↗
Str: 64Inf: 1
Dan Foord ↗
Str: 9Inf: 1

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

Outbound Tags (1)
Man Must Die
Inbound Posts (1)
Man Must Die
Last calculated: Jun 25, 7:16 AM
41

Related Content

No related content found.