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Analyzing Network Connections...

Loading Map...

Nearest Locations

  • 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
  • Thumbnail for Minsk
    Minsk0.0 km away

Network Profile

Overall Strength
i
70.21% of network
(10.11B)
Strength Breakdown
  • This Post (70.21%)
  • Vitebsk (2.65%)
  • Minsk (1.77%)
  • Brest (1.18%)
  • Gomel (1.18%)
  • Grodno (1.18%)
  • Mogilev (1.18%)
  • Jēkabpils (1.18%)
  • LVA (1.18%)
  • Hiking in Latvia (0.59%)
  • Objects in Latvia (0.59%)
  • Daugavpils (0.29%)
  • Jūrmala (0.29%)
  • Liepāja (0.29%)
  • Rēzekne (0.29%)
  • Riga (0.29%)
  • Valmiera (0.29%)
  • Ventspils (0.29%)
  • Ruba (0.29%)
  • Viciebsk Castle (0.29%)
  • Symbols of Jēkabpils (0.29%)
Dominant nodes (excluded from chart)
Belarus 14.16%
Influence Score
i
4.96% of network
(1.37)
Influence Breakdown
  • This Post (4.96%)
  • LVA (16.35%)
  • Minsk (6.13%)
  • Brest (4.09%)
  • Gomel (4.09%)
  • Grodno (4.09%)
  • Mogilev (4.09%)
  • Vitebsk (4.09%)
  • Daugavpils (4.09%)
  • Jēkabpils (4.09%)
  • Jūrmala (4.09%)
  • Liepāja (4.09%)
  • Rēzekne (4.09%)
  • Riga (4.09%)
  • Valmiera (4.09%)
  • Ventspils (4.09%)
  • Ruba (4.09%)
  • Viciebsk Castle (4.09%)
  • Symbols of Jēkabpils (4.09%)
  • Belarus (3.07%)
  • Hiking in Latvia (2.04%)
  • Objects in Latvia (2.04%)
Direct Connections 31

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, 17) = 17
$outbound = max(1, 14) = 14

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 17 * 14 = 238
Base_Influence (IV) = $inbound / $outbound = 17 / 14 = 1.2143

// 3. Exponential Network Values (accumulating 21 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 238 *
                           ( 4 [LVA] *
                            6 [Minsk] *
                            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 [Viciebsk Castle] *
                            1 [Symbols of Jēkabpils] *
                            48 [Belarus] *
                            2 [Hiking in Latvia] *
                            2 [Objects in Latvia]
                           )

                         = 10.11B

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1.2143 *
                           ( 4 [LVA] *
                            1.5 [Minsk] *
                            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 [Viciebsk Castle] *
                            1 [Symbols of Jēkabpils] *
                            0.75 [Belarus] *
                            0.5 [Hiking in Latvia] *
                            0.5 [Objects in Latvia]
                           )

                         = 1.37
Outbound 17 Tags on post
Inbound 14 Posts tagging this
Connections 21 Total nodes
Base Node Strength 238
Base Node Influence 1.2143
Strength Share (vs Direct Neighbours)
70.21% (10.11B overall)
  • This Post (70.21%)
  • Vitebsk (2.65%)
  • Minsk (1.77%)
  • Brest (1.18%)
  • Gomel (1.18%)
  • Grodno (1.18%)
  • Mogilev (1.18%)
  • Jēkabpils (1.18%)
  • LVA (1.18%)
  • Hiking in Latvia (0.59%)
  • Objects in Latvia (0.59%)
  • Daugavpils (0.29%)
  • Jūrmala (0.29%)
  • Liepāja (0.29%)
  • Rēzekne (0.29%)
  • Riga (0.29%)
  • Valmiera (0.29%)
  • Ventspils (0.29%)
  • Ruba (0.29%)
  • Viciebsk Castle (0.29%)
  • Symbols of Jēkabpils (0.29%)
Dominant nodes (excluded from chart)
Belarus 14.16%
Influence Share (vs Direct Neighbours)
4.96% (1.37 overall)
  • This Post (4.96%)
  • LVA (16.35%)
  • Minsk (6.13%)
  • Brest (4.09%)
  • Gomel (4.09%)
  • Grodno (4.09%)
  • Mogilev (4.09%)
  • Vitebsk (4.09%)
  • Daugavpils (4.09%)
  • Jēkabpils (4.09%)
  • Jūrmala (4.09%)
  • Liepāja (4.09%)
  • Rēzekne (4.09%)
  • Riga (4.09%)
  • Valmiera (4.09%)
  • Ventspils (4.09%)
  • Ruba (4.09%)
  • Viciebsk Castle (4.09%)
  • Symbols of Jēkabpils (4.09%)
  • Belarus (3.07%)
  • Hiking in Latvia (2.04%)
  • Objects in Latvia (2.04%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
LVA ↗
Str: 4Inf: 4
Minsk ↗
Str: 6Inf: 1.5
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
Viciebsk Castle ↗
Str: 1Inf: 1
Symbols of Jēkabpils ↗
Str: 1Inf: 1
Belarus ↗
Str: 48Inf: 0.75
Hiking in Latvia ↗
Str: 2Inf: 0.5
Objects in Latvia ↗
Str: 2Inf: 0.5
Weakest Connections (Lowest Multipliers)
Objects in Latvia ↗
Str: 2Inf: 0.5
Hiking in Latvia ↗
Str: 2Inf: 0.5
Belarus ↗
Str: 48Inf: 0.75
Symbols of Jēkabpils ↗
Str: 1Inf: 1
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
Vitebsk ↗
Str: 9Inf: 1
Mogilev ↗
Str: 4Inf: 1
Grodno ↗
Str: 4Inf: 1
Gomel ↗
Str: 4Inf: 1
Brest ↗
Str: 4Inf: 1
Minsk ↗
Str: 6Inf: 1.5
LVA ↗
Str: 4Inf: 4

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

Outbound Tags (17)
Belarus
BROKEN LINK
Brest
Daugavpils
Gomel
Grodno
Hiking in Latvia
BROKEN LINK
Jūrmala
Jēkabpils
Liepāja
Minsk
Mogilev
Objects in Latvia
BROKEN LINK
Riga
Rēzekne
Valmiera
Ventspils
Vitebsk
Inbound Posts (14)
Brest
Gomel
Grodno
Minsk
Mogilev
Vitebsk
Daugavpils
Jēkabpils
Jūrmala
Liepāja
Rēzekne
Riga
Valmiera
Ventspils
Last calculated: Oct 22, 1:17 PM
Vitsebsk Region, Belarus143

Related Content

Locations

  • LVA
  • Ruba
  • Viciebsk Castle

Nations

  • Belarus

Regionals

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

Sorters

  • Hiking in Latvia
  • Objects in Latvia

Topics

  • Symbols of Jēkabpils

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