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Pardubice

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Related Images

Hradec Králové
Military of Pardubice
South Moravian
Prague
Structures in Pardubice
Organizations of Pardubice
Night in Pardubice
South Bohemian
Micromobility in Czech Republic
Vysočina
Zlín
Ústí nad Labem
Plzeň
Moravian-Silesian
Sports in Pardubice
Liberec
Central Bohemian
Olomouc
Karlovy Vary

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Hradec Králové
    Hradec Králové19.4 km away
  • 📍
    Sculpture of Krakonoš in Hořice37.8 km away
  • 📍
    Fraxinus americana in Velešice40.0 km away
  • 📍
    Vidick45.6 km away
  • 📍
    Hrašeho 1150.2 km away

Network Profile

Overall Strength
i
0.40% of network
(28.8K)
Strength Breakdown
  • This Post (0.40%)
  • Karlovy Vary (1.61%)
  • Prague (1.61%)
  • Liberec (0.80%)
  • Plzeň (0.80%)
  • South Bohemian (0.80%)
  • Central Bohemian (0.40%)
  • Hradec Králové (0.40%)
  • Moravian-Silesian (0.40%)
  • Olomouc (0.40%)
  • South Moravian (0.40%)
  • Ústí nad Labem (0.40%)
  • Vysočina (0.40%)
  • Zlín (0.40%)
  • Česko (0.40%)
Dominant nodes (excluded from chart)
Czech Republic 90.36%
Influence Score
i
5.26% of network
(8)
Influence Breakdown
  • This Post (5.26%)
  • Liberec (10.53%)
  • Plzeň (10.53%)
  • South Bohemian (10.53%)
  • Czech Republic (5.26%)
  • Central Bohemian (5.26%)
  • Hradec Králové (5.26%)
  • Karlovy Vary (5.26%)
  • Moravian-Silesian (5.26%)
  • Olomouc (5.26%)
  • Prague (5.26%)
  • South Moravian (5.26%)
  • Ústí nad Labem (5.26%)
  • Vysočina (5.26%)
  • Zlín (5.26%)
  • Česko (5.26%)
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 15 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 2 [Liberec] *
                            2 [Plzeň] *
                            2 [South Bohemian] *
                            225 [Czech Republic] *
                            1 [Central Bohemian] *
                            1 [Hradec Králové] *
                            4 [Karlovy Vary] *
                            1 [Moravian-Silesian] *
                            1 [Olomouc] *
                            4 [Prague] *
                            1 [South Moravian] *
                            1 [Ústí nad Labem] *
                            1 [Vysočina] *
                            1 [Zlín] *
                            1 [Česko]
                           )

                         = 28.8K

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 2 [Liberec] *
                            2 [Plzeň] *
                            2 [South Bohemian] *
                            1 [Czech Republic] *
                            1 [Central Bohemian] *
                            1 [Hradec Králové] *
                            1 [Karlovy Vary] *
                            1 [Moravian-Silesian] *
                            1 [Olomouc] *
                            1 [Prague] *
                            1 [South Moravian] *
                            1 [Ústí nad Labem] *
                            1 [Vysočina] *
                            1 [Zlín] *
                            1 [Česko]
                           )

                         = 8
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 15 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.40% (28.8K overall)
  • This Post (0.40%)
  • Karlovy Vary (1.61%)
  • Prague (1.61%)
  • Liberec (0.80%)
  • Plzeň (0.80%)
  • South Bohemian (0.80%)
  • Central Bohemian (0.40%)
  • Hradec Králové (0.40%)
  • Moravian-Silesian (0.40%)
  • Olomouc (0.40%)
  • South Moravian (0.40%)
  • Ústí nad Labem (0.40%)
  • Vysočina (0.40%)
  • Zlín (0.40%)
  • Česko (0.40%)
Dominant nodes (excluded from chart)
Czech Republic 90.36%
Influence Share (vs Direct Neighbours)
5.26% (8 overall)
  • This Post (5.26%)
  • Liberec (10.53%)
  • Plzeň (10.53%)
  • South Bohemian (10.53%)
  • Czech Republic (5.26%)
  • Central Bohemian (5.26%)
  • Hradec Králové (5.26%)
  • Karlovy Vary (5.26%)
  • Moravian-Silesian (5.26%)
  • Olomouc (5.26%)
  • Prague (5.26%)
  • South Moravian (5.26%)
  • Ústí nad Labem (5.26%)
  • Vysočina (5.26%)
  • Zlín (5.26%)
  • Česko (5.26%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Liberec ↗
Str: 2Inf: 2
Plzeň ↗
Str: 2Inf: 2
South Bohemian ↗
Str: 2Inf: 2
Czech Republic ↗
Str: 225Inf: 1
Central Bohemian ↗
Str: 1Inf: 1
Hradec Králové ↗
Str: 1Inf: 1
Karlovy Vary ↗
Str: 4Inf: 1
Moravian-Silesian ↗
Str: 1Inf: 1
Olomouc ↗
Str: 1Inf: 1
Prague ↗
Str: 4Inf: 1
South Moravian ↗
Str: 1Inf: 1
Ústí nad Labem ↗
Str: 1Inf: 1
Vysočina ↗
Str: 1Inf: 1
Zlín ↗
Str: 1Inf: 1
Česko ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Česko ↗
Str: 1Inf: 1
Zlín ↗
Str: 1Inf: 1
Vysočina ↗
Str: 1Inf: 1
Ústí nad Labem ↗
Str: 1Inf: 1
South Moravian ↗
Str: 1Inf: 1
Prague ↗
Str: 4Inf: 1
Olomouc ↗
Str: 1Inf: 1
Moravian-Silesian ↗
Str: 1Inf: 1
Karlovy Vary ↗
Str: 4Inf: 1
Hradec Králové ↗
Str: 1Inf: 1
Central Bohemian ↗
Str: 1Inf: 1
Czech Republic ↗
Str: 225Inf: 1
South Bohemian ↗
Str: 2Inf: 2
Plzeň ↗
Str: 2Inf: 2
Liberec ↗
Str: 2Inf: 2

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

Outbound Tags (1)
Czech Republic
Inbound Posts (1)
Czech Republic
Last calculated: Sep 4, 6:39 PM
Pardubice, Pardubice Region, Czechia38

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