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Vitebsk

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Related Images

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Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Viciebsk Castle
    Viciebsk Castle0.3 km away
  • 📍
    Ruba13.8 km away
  • 📍
    Batali23.2 km away
  • Thumbnail for Latvia
    Latvia91.0 km away
  • Thumbnail for Rēzekne
    Rēzekne91.0 km away

Network Profile

Overall Strength
i
2.73% of network
(631.7M)
Strength Breakdown
  • This Post (2.73%)
  • Minsk (1.82%)
  • Brest (1.21%)
  • Gomel (1.21%)
  • Grodno (1.21%)
  • Mogilev (1.21%)
  • Jēkabpils (1.21%)
  • Daugavpils (0.30%)
  • Jūrmala (0.30%)
  • Liepāja (0.30%)
  • Rēzekne (0.30%)
  • Riga (0.30%)
  • Valmiera (0.30%)
  • Ventspils (0.30%)
  • Ruba (0.30%)
  • Viciebsk Castle (0.30%)
Dominant nodes (excluded from chart)
Latvia 72.12%Belarus 14.55%
Influence Score
i
5.42% of network
(1.37)
Influence Breakdown
  • This Post (5.42%)
  • Minsk (8.12%)
  • Latvia (6.58%)
  • Brest (5.42%)
  • Gomel (5.42%)
  • Grodno (5.42%)
  • Mogilev (5.42%)
  • Daugavpils (5.42%)
  • Jēkabpils (5.42%)
  • Jūrmala (5.42%)
  • Liepāja (5.42%)
  • Rēzekne (5.42%)
  • Riga (5.42%)
  • Valmiera (5.42%)
  • Ventspils (5.42%)
  • Ruba (5.42%)
  • Viciebsk Castle (5.42%)
  • Belarus (4.06%)
Direct Connections 6

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, 3) = 3

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 3 * 3 = 9
Base_Influence (IV) = $inbound / $outbound = 3 / 3 = 1

// 3. Exponential Network Values (accumulating 17 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 9 *
                           ( 6 [Minsk] *
                            238 [Latvia] *
                            4 [Brest] *
                            4 [Gomel] *
                            4 [Grodno] *
                            4 [Mogilev] *
                            1 [Daugavpils] *
                            4 [Jēkabpils] *
                            1 [Jūrmala] *
                            1 [Liepāja] *
                            1 [Rēzekne] *
                            1 [Riga] *
                            1 [Valmiera] *
                            1 [Ventspils] *
                            1 [Ruba] *
                            1 [Viciebsk Castle] *
                            48 [Belarus]
                           )

                         = 631.7M

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1.5 [Minsk] *
                            1.21 [Latvia] *
                            1 [Brest] *
                            1 [Gomel] *
                            1 [Grodno] *
                            1 [Mogilev] *
                            1 [Daugavpils] *
                            1 [Jēkabpils] *
                            1 [Jūrmala] *
                            1 [Liepāja] *
                            1 [Rēzekne] *
                            1 [Riga] *
                            1 [Valmiera] *
                            1 [Ventspils] *
                            1 [Ruba] *
                            1 [Viciebsk Castle] *
                            0.75 [Belarus]
                           )

                         = 1.37
Outbound 3 Tags on post
Inbound 3 Posts tagging this
Connections 17 Total nodes
Base Node Strength 9
Base Node Influence 1
Strength Share (vs Direct Neighbours)
2.73% (631.7M overall)
  • This Post (2.73%)
  • Minsk (1.82%)
  • Brest (1.21%)
  • Gomel (1.21%)
  • Grodno (1.21%)
  • Mogilev (1.21%)
  • Jēkabpils (1.21%)
  • Daugavpils (0.30%)
  • Jūrmala (0.30%)
  • Liepāja (0.30%)
  • Rēzekne (0.30%)
  • Riga (0.30%)
  • Valmiera (0.30%)
  • Ventspils (0.30%)
  • Ruba (0.30%)
  • Viciebsk Castle (0.30%)
Dominant nodes (excluded from chart)
Latvia 72.12%Belarus 14.55%
Influence Share (vs Direct Neighbours)
5.42% (1.37 overall)
  • This Post (5.42%)
  • Minsk (8.12%)
  • Latvia (6.58%)
  • Brest (5.42%)
  • Gomel (5.42%)
  • Grodno (5.42%)
  • Mogilev (5.42%)
  • Daugavpils (5.42%)
  • Jēkabpils (5.42%)
  • Jūrmala (5.42%)
  • Liepāja (5.42%)
  • Rēzekne (5.42%)
  • Riga (5.42%)
  • Valmiera (5.42%)
  • Ventspils (5.42%)
  • Ruba (5.42%)
  • Viciebsk Castle (5.42%)
  • Belarus (4.06%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Minsk ↗
Str: 6Inf: 1.5
Latvia ↗
Str: 238Inf: 1.21
Brest ↗
Str: 4Inf: 1
Gomel ↗
Str: 4Inf: 1
Grodno ↗
Str: 4Inf: 1
Mogilev ↗
Str: 4Inf: 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
Viciebsk Castle ↗
Str: 1Inf: 1
Belarus ↗
Str: 48Inf: 0.75
Weakest Connections (Lowest Multipliers)
Belarus ↗
Str: 48Inf: 0.75
Viciebsk Castle ↗
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
Mogilev ↗
Str: 4Inf: 1
Grodno ↗
Str: 4Inf: 1
Gomel ↗
Str: 4Inf: 1
Brest ↗
Str: 4Inf: 1
Latvia ↗
Str: 238Inf: 1.21
Minsk ↗
Str: 6Inf: 1.5

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

Outbound Tags (3)
Belarus
Latvia
Viciebsk Castle
Inbound Posts (3)
Latvia
Belarus
Viciebsk Castle
Last calculated: Sep 26, 4:41 PM
Vitsebsk, Vitsebsk Region, Belarus48

Related Content

Locations

  • Ruba
  • Viciebsk Castle

Nations

  • Belarus
  • Latvia

Regionals

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