Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Kaunas
Alytus
Lithuania
Vilnius
Marijampolė
Telšiai
Šiauliai
Utena
Panevėžys
Klaipėda

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 1 day ago
Comments: 0

Eileen Lally
Last login: 1 week ago
Comments: 0

Özkan Konu
Last login: 4 weeks ago
Comments: 0

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

Kevin Greene
Last login: 1 month ago
Comments: 0

Seán Millar
Last login: 1 month ago
Comments: 0

Tauragė

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

Alytus
Panevėžys
Kaunas
Klaipėda
Šiauliai
Vilnius
Utena
Telšiai
Marijampolė

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Telšiai
    Telšiai81.6 km away
  • 📍
    Labiau Castle86.2 km away
  • 📍
    Kreis Labiau86.6 km away
  • 📍
    Poljes86.6 km away
  • Thumbnail for Klaipėda
    Klaipėda88.8 km away

Network Profile

Overall Strength
i
0.72% of network
(2.2K)
Strength Breakdown
  • This Post (0.72%)
  • Vilnius (4.32%)
  • Panevėžys (2.16%)
  • Alytus (0.72%)
  • Kaunas (0.72%)
  • Klaipėda (0.72%)
  • Marijampolė (0.72%)
  • Šiauliai (0.72%)
  • Telšiai (0.72%)
  • Utena (0.72%)
  • Konstantinovo (0.72%)
Dominant nodes (excluded from chart)
Lithuania 87.05%
Influence Score
i
6.90% of network
(4.5)
Influence Breakdown
  • This Post (6.90%)
  • Panevėžys (20.69%)
  • Vilnius (10.34%)
  • Lithuania (6.90%)
  • Alytus (6.90%)
  • Kaunas (6.90%)
  • Klaipėda (6.90%)
  • Marijampolė (6.90%)
  • Šiauliai (6.90%)
  • Telšiai (6.90%)
  • Utena (6.90%)
  • Konstantinovo (6.90%)
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 11 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 3 [Panevėžys] *
                            6 [Vilnius] *
                            121 [Lithuania] *
                            1 [Alytus] *
                            1 [Kaunas] *
                            1 [Klaipėda] *
                            1 [Marijampolė] *
                            1 [Šiauliai] *
                            1 [Telšiai] *
                            1 [Utena] *
                            1 [Konstantinovo]
                           )

                         = 2.2K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 3 [Panevėžys] *
                            1.5 [Vilnius] *
                            1 [Lithuania] *
                            1 [Alytus] *
                            1 [Kaunas] *
                            1 [Klaipėda] *
                            1 [Marijampolė] *
                            1 [Šiauliai] *
                            1 [Telšiai] *
                            1 [Utena] *
                            1 [Konstantinovo]
                           )

                         = 4.5
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 11 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.72% (2.2K overall)
  • This Post (0.72%)
  • Vilnius (4.32%)
  • Panevėžys (2.16%)
  • Alytus (0.72%)
  • Kaunas (0.72%)
  • Klaipėda (0.72%)
  • Marijampolė (0.72%)
  • Šiauliai (0.72%)
  • Telšiai (0.72%)
  • Utena (0.72%)
  • Konstantinovo (0.72%)
Dominant nodes (excluded from chart)
Lithuania 87.05%
Influence Share (vs Direct Neighbours)
6.90% (4.5 overall)
  • This Post (6.90%)
  • Panevėžys (20.69%)
  • Vilnius (10.34%)
  • Lithuania (6.90%)
  • Alytus (6.90%)
  • Kaunas (6.90%)
  • Klaipėda (6.90%)
  • Marijampolė (6.90%)
  • Šiauliai (6.90%)
  • Telšiai (6.90%)
  • Utena (6.90%)
  • Konstantinovo (6.90%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Panevėžys ↗
Str: 3Inf: 3
Vilnius ↗
Str: 6Inf: 1.5
Lithuania ↗
Str: 121Inf: 1
Alytus ↗
Str: 1Inf: 1
Kaunas ↗
Str: 1Inf: 1
Klaipėda ↗
Str: 1Inf: 1
Marijampolė ↗
Str: 1Inf: 1
Šiauliai ↗
Str: 1Inf: 1
Telšiai ↗
Str: 1Inf: 1
Utena ↗
Str: 1Inf: 1
Konstantinovo ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Konstantinovo ↗
Str: 1Inf: 1
Utena ↗
Str: 1Inf: 1
Telšiai ↗
Str: 1Inf: 1
Šiauliai ↗
Str: 1Inf: 1
Marijampolė ↗
Str: 1Inf: 1
Klaipėda ↗
Str: 1Inf: 1
Kaunas ↗
Str: 1Inf: 1
Alytus ↗
Str: 1Inf: 1
Lithuania ↗
Str: 121Inf: 1
Vilnius ↗
Str: 6Inf: 1.5
Panevėžys ↗
Str: 3Inf: 3

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

Outbound Tags (1)
lithuania
Inbound Posts (1)
Lithuania
Last calculated: Jun 15, 3:30 AM
Tauragė, Tauragės miesto seniūnija, Lithuania24

Related Content

Locations

  • Konstantinovo

Nations

  • Lithuania

Regionals

  • Kaunas
  • Klaipėda
  • Marijampolė
  • Panevėžys
  • Šiauliai
  • Telšiai
  • Utena
  • Alytus
  • Vilnius