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Kansai region
Nara prefectureHyōgo prefectureOsaka prefectureKyoto metropolitan areaIse-Shima National ParkAgo BayDaiozakiMie Island

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Mie

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Related Images

Kinki Natural Trail
Yokoyama Viewpoint
Kansai dialects
Buses in Kinki region
Kansai Electric Power Company
Legendary creatures from Kansai region

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Kansai region
    Kansai region6.9 km away
  • Thumbnail for Yoro Park
    Yoro Park27.2 km away
  • 📍
    Koka Ninja Village28.2 km away
  • 📍
    Koka Ninja House31.5 km away
  • 📍
    Sea Life Nagoya33.7 km away

Network Profile

Overall Strength
i
0.59% of network
(1.22B)
Strength Breakdown
  • This Post (0.59%)
  • Nara prefecture (32.26%)
  • Kansai region (14.66%)
  • Ago Bay (4.69%)
  • Ise-Shima National Park (3.52%)
  • Kyoto metropolitan area (1.17%)
  • Osaka prefecture (0.29%)
  • Daiozaki (0.29%)
  • Mie Island (0.29%)
Dominant nodes (excluded from chart)
Hyōgo prefecture 42.23%
Influence Score
i
16.88% of network
(3.3)
Influence Breakdown
  • This Post (16.88%)
  • Kansai region (16.88%)
  • Nara prefecture (9.28%)
  • Hyōgo prefecture (8.44%)
  • Kyoto metropolitan area (8.44%)
  • Osaka prefecture (8.44%)
  • Ago Bay (8.44%)
  • Daiozaki (8.44%)
  • Mie Island (8.44%)
  • Ise-Shima National Park (6.33%)
Direct Connections 3

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, 1) = 1

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

// 3. Exponential Network Values (accumulating 9 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 2 *
                           ( 50 [Kansai region] *
                            110 [Nara prefecture] *
                            144 [Hyōgo prefecture] *
                            4 [Kyoto metropolitan area] *
                            1 [Osaka prefecture] *
                            16 [Ago Bay] *
                            1 [Daiozaki] *
                            1 [Mie Island] *
                            12 [Ise-Shima National Park]
                           )

                         = 1.22B

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 2 *
                           ( 2 [Kansai region] *
                            1.1 [Nara prefecture] *
                            1 [Hyōgo prefecture] *
                            1 [Kyoto metropolitan area] *
                            1 [Osaka prefecture] *
                            1 [Ago Bay] *
                            1 [Daiozaki] *
                            1 [Mie Island] *
                            0.75 [Ise-Shima National Park]
                           )

                         = 3.3
Outbound 2 Tags on post
Inbound 1 Posts tagging this
Connections 9 Total nodes
Base Node Strength 2
Base Node Influence 2
Strength Share (vs Direct Neighbours)
0.59% (1.22B overall)
  • This Post (0.59%)
  • Nara prefecture (32.26%)
  • Kansai region (14.66%)
  • Ago Bay (4.69%)
  • Ise-Shima National Park (3.52%)
  • Kyoto metropolitan area (1.17%)
  • Osaka prefecture (0.29%)
  • Daiozaki (0.29%)
  • Mie Island (0.29%)
Dominant nodes (excluded from chart)
Hyōgo prefecture 42.23%
Influence Share (vs Direct Neighbours)
16.88% (3.3 overall)
  • This Post (16.88%)
  • Kansai region (16.88%)
  • Nara prefecture (9.28%)
  • Hyōgo prefecture (8.44%)
  • Kyoto metropolitan area (8.44%)
  • Osaka prefecture (8.44%)
  • Ago Bay (8.44%)
  • Daiozaki (8.44%)
  • Mie Island (8.44%)
  • Ise-Shima National Park (6.33%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Kansai region ↗
Str: 50Inf: 2
Nara prefecture ↗
Str: 110Inf: 1.1
Hyōgo prefecture ↗
Str: 144Inf: 1
Kyoto metropolitan area ↗
Str: 4Inf: 1
Osaka prefecture ↗
Str: 1Inf: 1
Ago Bay ↗
Str: 16Inf: 1
Daiozaki ↗
Str: 1Inf: 1
Mie Island ↗
Str: 1Inf: 1
Ise-Shima National Park ↗
Str: 12Inf: 0.75
Weakest Connections (Lowest Multipliers)
Ise-Shima National Park ↗
Str: 12Inf: 0.75
Mie Island ↗
Str: 1Inf: 1
Daiozaki ↗
Str: 1Inf: 1
Ago Bay ↗
Str: 16Inf: 1
Osaka prefecture ↗
Str: 1Inf: 1
Kyoto metropolitan area ↗
Str: 4Inf: 1
Hyōgo prefecture ↗
Str: 144Inf: 1
Nara prefecture ↗
Str: 110Inf: 1.1
Kansai region ↗
Str: 50Inf: 2

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

Outbound Tags (2)
Ise-Shima National Park
BROKEN LINK
Kansai region
Inbound Posts (1)
Kansai region
Last calculated: Jun 21, 10:29 AM
Komono, Mie County, Japan28

Related Content

Locations

  • Kansai region
  • Hyōgo prefecture
  • Kyoto metropolitan area
  • Nara prefecture
  • Osaka prefecture

Topics

  • Mie Island
  • Ise-Shima National Park
  • Ago Bay
  • Daiozaki