Skip to content

Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Frankie Goes to Hollywood
Brian Nash

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 2 days ago
Comments: 0

Francesca Ladybird
Last login: 2 months ago
Comments: 0

Matthew Leech
Last login: 3 months ago
Comments: 1

Jessica
Last login: 3 months ago
Comments: 0

Darragh Lennon
Last login: 3 months ago
Comments: 0

Cathal Kennedy
Last login: 3 months ago
Comments: 0

Low (12)

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

  • Frankie Goes to Hollywood
    Frankie Goes to Hollywood band photo

Connected Musicians

  • Brian Nash

Analyzing Network Connections...

Network Profile

Overall Strength
i
1.45% of network
(256)
Strength Breakdown
  • This Post (1.45%)
  • Frankie Goes to Hollywood (92.75%)
  • Brian Nash (5.80%)
Influence Score
i
33.33% of network
(1)
Influence Breakdown
  • This Post (33.33%)
  • Frankie Goes to Hollywood (33.33%)
  • Brian Nash (33.33%)
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 2 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 64 [Frankie Goes to Hollywood] *
                            4 [Brian Nash]
                           )

                         = 256

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Frankie Goes to Hollywood] *
                            1 [Brian Nash]
                           )

                         = 1
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 2 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
1.45% (256 overall)
  • This Post (1.45%)
  • Frankie Goes to Hollywood (92.75%)
  • Brian Nash (5.80%)
Influence Share (vs Direct Neighbours)
33.33% (1 overall)
  • This Post (33.33%)
  • Frankie Goes to Hollywood (33.33%)
  • Brian Nash (33.33%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Frankie Goes to Hollywood ↗
Str: 64Inf: 1
Brian Nash ↗
Str: 4Inf: 1
Weakest Connections (Lowest Multipliers)
Brian Nash ↗
Str: 4Inf: 1
Frankie Goes to Hollywood ↗
Str: 64Inf: 1

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

Outbound Tags (1)
Brian Nash
Inbound Posts (1)
Brian Nash
Last calculated: Oct 26, 4:04 PM
21

Related Content

No related content found.

A Muso community