Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Latvia
Belarus
Liepāja
Riga
Jēkabpils
Ventspils
Vitebsk
Grodno
Mogilev
Daugavpils

Recent Logins

View Members Directory

Jessica
Last login: 4 hours ago
Comments: 0

Tadhg Kelleher
Last login: 11 hours ago
Comments: 0

Darragh Lennon
Last login: 1 week ago
Comments: 0

Cathal Kennedy
Last login: 2 weeks ago
Comments: 0

jacierlogyn
Last login: 1 month ago
Comments: 0

Eileen Lally
Last login: 2 months ago
Comments: 0

Minsk

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

Molchat-Doma-Discoteque-Official-Music-Video-Молчат-Дома-Дискотека
Daugavpils
Belarus-Folk-Music
Objects in Latvia
Vitebsk
Mogilev
Rēzekne
Valmiera
Ventspils
Military of Belarus
Metro-Goldwyn-Mayer
Riga
Hiking in Latvia
Jūrmala
Gomel
Grodno
Lithuania in Russo-Ukrainian War
Brest
Liepāja
Society of Latvia
Jēkabpils
Jelgava

Connected Bands/Artists

  • Irving Thalberg

Connected Musicians

  • Louis B. Mayer

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Latvia
    Latvia0.0 km away
  • Thumbnail for Rēzekne
    Rēzekne0.0 km away
  • Thumbnail for Ventspils
    Ventspils0.0 km away
  • Thumbnail for Daugavpils
    Daugavpils0.0 km away
  • Thumbnail for Jūrmala
    Jūrmala0.0 km away

Network Profile

Overall Strength
i
1.81% of network
(1.26B)
Strength Breakdown
  • This Post (1.81%)
  • Vitebsk (2.71%)
  • Brest (1.20%)
  • Gomel (1.20%)
  • Grodno (1.20%)
  • Mogilev (1.20%)
  • Jēkabpils (1.20%)
  • Louis B. Mayer (0.60%)
  • Daugavpils (0.30%)
  • Jūrmala (0.30%)
  • Liepāja (0.30%)
  • Rēzekne (0.30%)
  • Riga (0.30%)
  • Valmiera (0.30%)
  • Ventspils (0.30%)
  • Ruba (0.30%)
  • Irving Thalberg (0.30%)
Dominant nodes (excluded from chart)
Latvia 71.69%Belarus 14.46%
Influence Score
i
7.91% of network
(0.683)
Influence Breakdown
  • This Post (7.91%)
  • Latvia (6.40%)
  • Brest (5.27%)
  • Gomel (5.27%)
  • Grodno (5.27%)
  • Mogilev (5.27%)
  • Vitebsk (5.27%)
  • Daugavpils (5.27%)
  • Jēkabpils (5.27%)
  • Jūrmala (5.27%)
  • Liepāja (5.27%)
  • Rēzekne (5.27%)
  • Riga (5.27%)
  • Valmiera (5.27%)
  • Ventspils (5.27%)
  • Ruba (5.27%)
  • Irving Thalberg (5.27%)
  • Belarus (3.95%)
  • Louis B. Mayer (2.64%)
Direct Connections 5

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, 3) = 3
$outbound = max(1, 2) = 2

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 3 * 2 = 6
Base_Influence (IV) = $inbound / $outbound = 3 / 2 = 1.5

// 3. Exponential Network Values (accumulating 18 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 6 *
                           ( 238 [Latvia] *
                            4 [Brest] *
                            4 [Gomel] *
                            4 [Grodno] *
                            4 [Mogilev] *
                            9 [Vitebsk] *
                            1 [Daugavpils] *
                            4 [Jēkabpils] *
                            1 [Jūrmala] *
                            1 [Liepāja] *
                            1 [Rēzekne] *
                            1 [Riga] *
                            1 [Valmiera] *
                            1 [Ventspils] *
                            1 [Ruba] *
                            1 [Irving Thalberg] *
                            48 [Belarus] *
                            2 [Louis B. Mayer]
                           )

                         = 1.26B

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1.5 *
                           ( 1.21 [Latvia] *
                            1 [Brest] *
                            1 [Gomel] *
                            1 [Grodno] *
                            1 [Mogilev] *
                            1 [Vitebsk] *
                            1 [Daugavpils] *
                            1 [Jēkabpils] *
                            1 [Jūrmala] *
                            1 [Liepāja] *
                            1 [Rēzekne] *
                            1 [Riga] *
                            1 [Valmiera] *
                            1 [Ventspils] *
                            1 [Ruba] *
                            1 [Irving Thalberg] *
                            0.75 [Belarus] *
                            0.5 [Louis B. Mayer]
                           )

                         = 0.683
Outbound 3 Tags on post
Inbound 2 Posts tagging this
Connections 18 Total nodes
Base Node Strength 6
Base Node Influence 1.5
Strength Share (vs Direct Neighbours)
1.81% (1.26B overall)
  • This Post (1.81%)
  • Vitebsk (2.71%)
  • Brest (1.20%)
  • Gomel (1.20%)
  • Grodno (1.20%)
  • Mogilev (1.20%)
  • Jēkabpils (1.20%)
  • Louis B. Mayer (0.60%)
  • Daugavpils (0.30%)
  • Jūrmala (0.30%)
  • Liepāja (0.30%)
  • Rēzekne (0.30%)
  • Riga (0.30%)
  • Valmiera (0.30%)
  • Ventspils (0.30%)
  • Ruba (0.30%)
  • Irving Thalberg (0.30%)
Dominant nodes (excluded from chart)
Latvia 71.69%Belarus 14.46%
Influence Share (vs Direct Neighbours)
7.91% (0.683 overall)
  • This Post (7.91%)
  • Latvia (6.40%)
  • Brest (5.27%)
  • Gomel (5.27%)
  • Grodno (5.27%)
  • Mogilev (5.27%)
  • Vitebsk (5.27%)
  • Daugavpils (5.27%)
  • Jēkabpils (5.27%)
  • Jūrmala (5.27%)
  • Liepāja (5.27%)
  • Rēzekne (5.27%)
  • Riga (5.27%)
  • Valmiera (5.27%)
  • Ventspils (5.27%)
  • Ruba (5.27%)
  • Irving Thalberg (5.27%)
  • Belarus (3.95%)
  • Louis B. Mayer (2.64%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Latvia ↗
Str: 238Inf: 1.21
Brest ↗
Str: 4Inf: 1
Gomel ↗
Str: 4Inf: 1
Grodno ↗
Str: 4Inf: 1
Mogilev ↗
Str: 4Inf: 1
Vitebsk ↗
Str: 9Inf: 1
Daugavpils ↗
Str: 1Inf: 1
Jēkabpils ↗
Str: 4Inf: 1
Jūrmala ↗
Str: 1Inf: 1
Liepāja ↗
Str: 1Inf: 1
Rēzekne ↗
Str: 1Inf: 1
Riga ↗
Str: 1Inf: 1
Valmiera ↗
Str: 1Inf: 1
Ventspils ↗
Str: 1Inf: 1
Ruba ↗
Str: 1Inf: 1
Irving Thalberg ↗
Str: 1Inf: 1
Belarus ↗
Str: 48Inf: 0.75
Louis B. Mayer ↗
Str: 2Inf: 0.5
Weakest Connections (Lowest Multipliers)
Louis B. Mayer ↗
Str: 2Inf: 0.5
Belarus ↗
Str: 48Inf: 0.75
Irving Thalberg ↗
Str: 1Inf: 1
Ruba ↗
Str: 1Inf: 1
Ventspils ↗
Str: 1Inf: 1
Valmiera ↗
Str: 1Inf: 1
Riga ↗
Str: 1Inf: 1
Rēzekne ↗
Str: 1Inf: 1
Liepāja ↗
Str: 1Inf: 1
Jūrmala ↗
Str: 1Inf: 1
Jēkabpils ↗
Str: 4Inf: 1
Daugavpils ↗
Str: 1Inf: 1
Vitebsk ↗
Str: 9Inf: 1
Mogilev ↗
Str: 4Inf: 1
Grodno ↗
Str: 4Inf: 1
Gomel ↗
Str: 4Inf: 1
Brest ↗
Str: 4Inf: 1
Latvia ↗
Str: 238Inf: 1.21

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

Outbound Tags (3)
Belarus
Latvia
Louis B. Mayer
BROKEN LINK
Inbound Posts (2)
Latvia
Belarus
Last calculated: Jul 30, 1:33 AM
Vitsebsk Region, Belarus122

Related Content

Locations

  • Ruba

Nations

  • Belarus
  • Latvia

Regionals

  • Daugavpils
  • Jēkabpils
  • Jūrmala
  • Brest
  • Liepāja
  • Gomel
  • Rēzekne
  • Grodno
  • Riga
  • Mogilev
  • Valmiera
  • Vitebsk
  • Ventspils