Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Latvia
Minsk
Belarus
Liepāja
Riga
Jēkabpils
Vitebsk
Alexander Lukashenko
Grodno
Valmiera

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 1 day ago
Comments: 0

Eileen Lally
Last login: 5 days ago
Comments: 0

Özkan Konu
Last login: 3 weeks ago
Comments: 0

Anne Marie Bevan
Last login: 4 weeks ago
Comments: 0

Kevin Greene
Last login: 4 weeks ago
Comments: 0

Seán Millar
Last login: 1 month ago
Comments: 0

Mogilev

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
Gomel
Belarus-Folk-Music
Jēkabpils
Riga
Liepāja
Jelgava
Lithuania in Russo-Ukrainian War
Military of Belarus
Rēzekne
Ventspils
Vitebsk
Judaism in Mahilioŭ
Society of Latvia
Objects in Latvia
Minsk
Jūrmala
Daugavpils
Brest
Hiking in Latvia
Valmiera
Grodno

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • 📍
    Gendarmerie barracks, Mahilioŭ0.2 km away
  • 📍
    Mahilioŭ Regional Puppet Theater0.2 km away
  • Thumbnail for Building of Peasant Land Bank, Mahilioŭ
    Building of Peasant Land Bank, Mahilioŭ0.3 km away
  • 📍
    Pažarny Lane 6, Mahilioŭ1.1 km away
  • 📍
    Fire station in Mahilioŭ1.1 km away

Network Profile

Overall Strength
i
1.02% of network
(3.71T)
Strength Breakdown
  • This Post (1.02%)
  • Alexander Lukashenko (8.88%)
  • Vitebsk (2.28%)
  • Grodno (2.03%)
  • Minsk (2.03%)
  • Gomel (1.52%)
  • Brest (1.02%)
  • Jēkabpils (1.02%)
  • Jūrmala (1.02%)
  • Rēzekne (1.02%)
  • Ventspils (0.51%)
  • Daugavpils (0.25%)
  • Liepāja (0.25%)
  • Riga (0.25%)
  • Valmiera (0.25%)
  • Ruba (0.25%)
Dominant nodes (excluded from chart)
Latvia 60.41%Belarus 15.99%
Influence Score
i
4.57% of network
(15.87)
Influence Breakdown
  • This Post (4.57%)
  • Grodno (9.14%)
  • Minsk (9.14%)
  • Ventspils (9.14%)
  • Gomel (6.85%)
  • Alexander Lukashenko (6.40%)
  • Latvia (5.55%)
  • Brest (4.57%)
  • Vitebsk (4.57%)
  • Daugavpils (4.57%)
  • Jēkabpils (4.57%)
  • Jūrmala (4.57%)
  • Liepāja (4.57%)
  • Rēzekne (4.57%)
  • Riga (4.57%)
  • Valmiera (4.57%)
  • Ruba (4.57%)
  • Belarus (3.55%)
Direct Connections 4

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

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 2 * 2 = 4
Base_Influence (IV) = $inbound / $outbound = 2 / 2 = 1

// 3. Exponential Network Values (accumulating 17 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 4 *
                           ( 8 [Grodno] *
                            8 [Minsk] *
                            2 [Ventspils] *
                            6 [Gomel] *
                            35 [Alexander Lukashenko] *
                            238 [Latvia] *
                            4 [Brest] *
                            9 [Vitebsk] *
                            1 [Daugavpils] *
                            4 [Jēkabpils] *
                            4 [Jūrmala] *
                            1 [Liepāja] *
                            4 [Rēzekne] *
                            1 [Riga] *
                            1 [Valmiera] *
                            1 [Ruba] *
                            63 [Belarus]
                           )

                         = 3.71T

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 2 [Grodno] *
                            2 [Minsk] *
                            2 [Ventspils] *
                            1.5 [Gomel] *
                            1.4 [Alexander Lukashenko] *
                            1.21 [Latvia] *
                            1 [Brest] *
                            1 [Vitebsk] *
                            1 [Daugavpils] *
                            1 [Jēkabpils] *
                            1 [Jūrmala] *
                            1 [Liepāja] *
                            1 [Rēzekne] *
                            1 [Riga] *
                            1 [Valmiera] *
                            1 [Ruba] *
                            0.7778 [Belarus]
                           )

                         = 15.87
Outbound 2 Tags on post
Inbound 2 Posts tagging this
Connections 17 Total nodes
Base Node Strength 4
Base Node Influence 1
Strength Share (vs Direct Neighbours)
1.02% (3.71T overall)
  • This Post (1.02%)
  • Alexander Lukashenko (8.88%)
  • Vitebsk (2.28%)
  • Grodno (2.03%)
  • Minsk (2.03%)
  • Gomel (1.52%)
  • Brest (1.02%)
  • Jēkabpils (1.02%)
  • Jūrmala (1.02%)
  • Rēzekne (1.02%)
  • Ventspils (0.51%)
  • Daugavpils (0.25%)
  • Liepāja (0.25%)
  • Riga (0.25%)
  • Valmiera (0.25%)
  • Ruba (0.25%)
Dominant nodes (excluded from chart)
Latvia 60.41%Belarus 15.99%
Influence Share (vs Direct Neighbours)
4.57% (15.87 overall)
  • This Post (4.57%)
  • Grodno (9.14%)
  • Minsk (9.14%)
  • Ventspils (9.14%)
  • Gomel (6.85%)
  • Alexander Lukashenko (6.40%)
  • Latvia (5.55%)
  • Brest (4.57%)
  • Vitebsk (4.57%)
  • Daugavpils (4.57%)
  • Jēkabpils (4.57%)
  • Jūrmala (4.57%)
  • Liepāja (4.57%)
  • Rēzekne (4.57%)
  • Riga (4.57%)
  • Valmiera (4.57%)
  • Ruba (4.57%)
  • Belarus (3.55%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Grodno ↗
Str: 8Inf: 2
Minsk ↗
Str: 8Inf: 2
Ventspils ↗
Str: 2Inf: 2
Gomel ↗
Str: 6Inf: 1.5
Alexander Lukashenko ↗
Str: 35Inf: 1.4
Latvia ↗
Str: 238Inf: 1.21
Brest ↗
Str: 4Inf: 1
Vitebsk ↗
Str: 9Inf: 1
Daugavpils ↗
Str: 1Inf: 1
Jēkabpils ↗
Str: 4Inf: 1
Jūrmala ↗
Str: 4Inf: 1
Liepāja ↗
Str: 1Inf: 1
Rēzekne ↗
Str: 4Inf: 1
Riga ↗
Str: 1Inf: 1
Valmiera ↗
Str: 1Inf: 1
Ruba ↗
Str: 1Inf: 1
Belarus ↗
Str: 63Inf: 0.7778
Weakest Connections (Lowest Multipliers)
Belarus ↗
Str: 63Inf: 0.7778
Ruba ↗
Str: 1Inf: 1
Valmiera ↗
Str: 1Inf: 1
Riga ↗
Str: 1Inf: 1
Rēzekne ↗
Str: 4Inf: 1
Liepāja ↗
Str: 1Inf: 1
Jūrmala ↗
Str: 4Inf: 1
Jēkabpils ↗
Str: 4Inf: 1
Daugavpils ↗
Str: 1Inf: 1
Vitebsk ↗
Str: 9Inf: 1
Brest ↗
Str: 4Inf: 1
Latvia ↗
Str: 238Inf: 1.21
Alexander Lukashenko ↗
Str: 35Inf: 1.4
Gomel ↗
Str: 6Inf: 1.5
Ventspils ↗
Str: 2Inf: 2
Minsk ↗
Str: 8Inf: 2
Grodno ↗
Str: 8Inf: 2

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

Outbound Tags (2)
Belarus
Latvia
Inbound Posts (2)
Latvia
Belarus
Last calculated: Jun 12, 12:51 AM
Mahilyow, Mahilyow Region, Belarus44

Related Content

Locations

  • Alexander Lukashenko
  • Ruba

Nations

  • Belarus
  • Latvia

Regionals

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