Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

SkálaPavel SkálaDneska prisel nový klukJakub

Recent Logins

View Members Directory

Francesca Ladybird
Last login: 2 days ago
Comments: 0

Tadhg Kelleher
Last login: 5 days ago
Comments: 0

Matthew Leech
Last login: 4 weeks ago
Comments: 1

Jessica
Last login: 1 month ago
Comments: 0

Darragh Lennon
Last login: 1 month ago
Comments: 0

Cathal Kennedy
Last login: 2 months ago
Comments: 0

Do zubu a do srdícka

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

Marsyas
Mezek

Network Profile

Overall Strength
i
1.33% of network
(896)
Strength Breakdown
  • This Post (1.33%)
  • Skála (74.67%)
  • Pavel Skála (21.33%)
  • Jakub (1.33%)
  • Dneska prisel nový kluk (1.33%)
Influence Score
i
19.44% of network
(1.14)
Influence Breakdown
  • This Post (19.44%)
  • Skála (22.22%)
  • Pavel Skála (19.44%)
  • Jakub (19.44%)
  • Dneska prisel nový kluk (19.44%)
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 4 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 56 [Skála] *
                            16 [Pavel Skála] *
                            1 [Jakub] *
                            1 [Dneska prisel nový kluk]
                           )

                         = 896

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1.14 [Skála] *
                            1 [Pavel Skála] *
                            1 [Jakub] *
                            1 [Dneska prisel nový kluk]
                           )

                         = 1.14
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 4 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
1.33% (896 overall)
  • This Post (1.33%)
  • Skála (74.67%)
  • Pavel Skála (21.33%)
  • Jakub (1.33%)
  • Dneska prisel nový kluk (1.33%)
Influence Share (vs Direct Neighbours)
19.44% (1.14 overall)
  • This Post (19.44%)
  • Skála (22.22%)
  • Pavel Skála (19.44%)
  • Jakub (19.44%)
  • Dneska prisel nový kluk (19.44%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Skála ↗
Str: 56Inf: 1.14
Pavel Skála ↗
Str: 16Inf: 1
Jakub ↗
Str: 1Inf: 1
Dneska prisel nový kluk ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Dneska prisel nový kluk ↗
Str: 1Inf: 1
Jakub ↗
Str: 1Inf: 1
Pavel Skála ↗
Str: 16Inf: 1
Skála ↗
Str: 56Inf: 1.14

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

Outbound Tags (1)
Pavel Skála
Inbound Posts (1)
Pavel Skála
Last calculated: Sep 2, 3:05 PM
17

Related Content

Figures

  • Pavel Skála

Topics

  • Skála
  • Jakub
  • Dneska prisel nový kluk