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Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Vitebsk
    Vitebsk13.8 km away
  • Thumbnail for Viciebsk Castle
    Viciebsk Castle13.9 km away
  • 📍
    Batali17.4 km away
  • Thumbnail for Latvia
    Latvia97.7 km away
  • Thumbnail for Rēzekne
    Rēzekne97.7 km away

Network Profile

Overall Strength
i
0.31% of network
(157.93M)
Strength Breakdown
  • This Post (0.31%)
  • Belarus (15.09%)
  • Vitebsk (2.83%)
  • Minsk (1.89%)
  • Brest (1.26%)
  • Gomel (1.26%)
  • Grodno (1.26%)
  • Mogilev (1.26%)
Dominant nodes (excluded from chart)
Latvia 74.84%
Influence Score
i
10.57% of network
(1.37)
Influence Breakdown
  • This Post (10.57%)
  • Minsk (15.85%)
  • Latvia (12.83%)
  • Brest (10.57%)
  • Gomel (10.57%)
  • Grodno (10.57%)
  • Mogilev (10.57%)
  • Vitebsk (10.57%)
  • Belarus (7.92%)
Direct Connections 1

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, 0) = 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 8 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 6 [Minsk] *
                            238 [Latvia] *
                            4 [Brest] *
                            4 [Gomel] *
                            4 [Grodno] *
                            4 [Mogilev] *
                            9 [Vitebsk] *
                            48 [Belarus]
                           )

                         = 157.93M

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 [Vitebsk] *
                            0.75 [Belarus]
                           )

                         = 1.37
Outbound 1 Tags on post
Inbound 0 Posts tagging this
Connections 8 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.31% (157.93M overall)
  • This Post (0.31%)
  • Belarus (15.09%)
  • Vitebsk (2.83%)
  • Minsk (1.89%)
  • Brest (1.26%)
  • Gomel (1.26%)
  • Grodno (1.26%)
  • Mogilev (1.26%)
Dominant nodes (excluded from chart)
Latvia 74.84%
Influence Share (vs Direct Neighbours)
10.57% (1.37 overall)
  • This Post (10.57%)
  • Minsk (15.85%)
  • Latvia (12.83%)
  • Brest (10.57%)
  • Gomel (10.57%)
  • Grodno (10.57%)
  • Mogilev (10.57%)
  • Vitebsk (10.57%)
  • Belarus (7.92%)

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
Vitebsk ↗
Str: 9Inf: 1
Belarus ↗
Str: 48Inf: 0.75
Weakest Connections (Lowest Multipliers)
Belarus ↗
Str: 48Inf: 0.75
Vitebsk ↗
Str: 9Inf: 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 (1)
Belarus
BROKEN LINK
Inbound Posts (0)
No other posts link to this one yet.
Last calculated: Sep 26, 3:29 AM
Vitsebsk, Vitsebsk Region, Belarus32

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