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Vilnius

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Analyzing Network Connections...

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Nearest Locations

  • 📍
    Vilnius Cathedral0.3 km away
  • 📍
    Cathedral Square0.4 km away
  • 📍
    Palace of the Grand Dukes of Lithuania0.4 km away
  • 📍
    Gediminas Monument in Vilnius0.4 km away
  • 📍
    Ukrainian Heroes2.8 km away

Network Profile

Overall Strength
i
2.68% of network
(46.5K)
Strength Breakdown
  • This Post (2.68%)
  • Saint Casimir (5.37%)
  • Kaziuko mugė (2.68%)
  • Panevėžys (2.01%)
  • Alytus (0.67%)
  • Kaunas (0.67%)
  • Klaipėda (0.67%)
  • Marijampolė (0.67%)
  • Šiauliai (0.67%)
  • Tauragė (0.67%)
  • Telšiai (0.67%)
  • Utena (0.67%)
  • Konstantinovo (0.67%)
Dominant nodes (excluded from chart)
Lithuania 81.21%
Influence Score
i
5.88% of network
(6)
Influence Breakdown
  • This Post (5.88%)
  • Panevėžys (17.65%)
  • Saint Casimir (11.76%)
  • Lithuania (5.88%)
  • Kaziuko mugė (5.88%)
  • Alytus (5.88%)
  • Kaunas (5.88%)
  • Klaipėda (5.88%)
  • Marijampolė (5.88%)
  • Šiauliai (5.88%)
  • Tauragė (5.88%)
  • Telšiai (5.88%)
  • Utena (5.88%)
  • Konstantinovo (5.88%)
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 13 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 4 *
                           ( 3 [Panevėžys] *
                            8 [Saint Casimir] *
                            121 [Lithuania] *
                            4 [Kaziuko mugė] *
                            1 [Alytus] *
                            1 [Kaunas] *
                            1 [Klaipėda] *
                            1 [Marijampolė] *
                            1 [Šiauliai] *
                            1 [Tauragė] *
                            1 [Telšiai] *
                            1 [Utena] *
                            1 [Konstantinovo]
                           )

                         = 46.5K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 3 [Panevėžys] *
                            2 [Saint Casimir] *
                            1 [Lithuania] *
                            1 [Kaziuko mugė] *
                            1 [Alytus] *
                            1 [Kaunas] *
                            1 [Klaipėda] *
                            1 [Marijampolė] *
                            1 [Šiauliai] *
                            1 [Tauragė] *
                            1 [Telšiai] *
                            1 [Utena] *
                            1 [Konstantinovo]
                           )

                         = 6
Outbound 2 Tags on post
Inbound 2 Posts tagging this
Connections 13 Total nodes
Base Node Strength 4
Base Node Influence 1
Strength Share (vs Direct Neighbours)
2.68% (46.5K overall)
  • This Post (2.68%)
  • Saint Casimir (5.37%)
  • Kaziuko mugė (2.68%)
  • Panevėžys (2.01%)
  • Alytus (0.67%)
  • Kaunas (0.67%)
  • Klaipėda (0.67%)
  • Marijampolė (0.67%)
  • Šiauliai (0.67%)
  • Tauragė (0.67%)
  • Telšiai (0.67%)
  • Utena (0.67%)
  • Konstantinovo (0.67%)
Dominant nodes (excluded from chart)
Lithuania 81.21%
Influence Share (vs Direct Neighbours)
5.88% (6 overall)
  • This Post (5.88%)
  • Panevėžys (17.65%)
  • Saint Casimir (11.76%)
  • Lithuania (5.88%)
  • Kaziuko mugė (5.88%)
  • Alytus (5.88%)
  • Kaunas (5.88%)
  • Klaipėda (5.88%)
  • Marijampolė (5.88%)
  • Šiauliai (5.88%)
  • Tauragė (5.88%)
  • Telšiai (5.88%)
  • Utena (5.88%)
  • Konstantinovo (5.88%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Panevėžys ↗
Str: 3Inf: 3
Saint Casimir ↗
Str: 8Inf: 2
Lithuania ↗
Str: 121Inf: 1
Kaziuko mugė ↗
Str: 4Inf: 1
Alytus ↗
Str: 1Inf: 1
Kaunas ↗
Str: 1Inf: 1
Klaipėda ↗
Str: 1Inf: 1
Marijampolė ↗
Str: 1Inf: 1
Šiauliai ↗
Str: 1Inf: 1
Tauragė ↗
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
Tauragė ↗
Str: 1Inf: 1
Šiauliai ↗
Str: 1Inf: 1
Marijampolė ↗
Str: 1Inf: 1
Klaipėda ↗
Str: 1Inf: 1
Kaunas ↗
Str: 1Inf: 1
Alytus ↗
Str: 1Inf: 1
Kaziuko mugė ↗
Str: 4Inf: 1
Lithuania ↗
Str: 121Inf: 1
Saint Casimir ↗
Str: 8Inf: 2
Panevėžys ↗
Str: 3Inf: 3

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

Outbound Tags (2)
Kaziuko mugė
lithuania
Inbound Posts (2)
Lithuania
Kaziuko mugė
Last calculated: Sep 26, 10:47 AM
Vilnius, Vilnius County, Lithuania51

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