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Harrow International School AppiCharles Theodore WilliamsWalter HeadlamHarrow International School Hong KongHarrow International School BeijingArnold HillsVictor PasmoreHarrow School Speech Room

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Harrow School Chapel

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Related Images

Granada Theatres
Alumni of Harrow School

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Harrow
    Harrow0.1 km away
  • Thumbnail for London Borough of Harrow
    London Borough of Harrow1.7 km away
  • 📍
    Horsenden Hill3.1 km away
  • 📍
    Ealing Road, Wembley4.1 km away
  • 📍
    Ealing Road4.1 km away

Network Profile

Overall Strength
i
0.93% of network
(99)
Strength Breakdown
  • This Post (0.93%)
  • Arnold Hills (0.93%)
  • Charles Theodore Williams (0.93%)
  • Harrow International School Appi (0.93%)
  • Harrow International School Beijing (0.93%)
  • Harrow International School Hong Kong (0.93%)
  • Harrow School Speech Room (0.93%)
  • Victor Pasmore (0.93%)
  • Walter Headlam (0.93%)
Dominant nodes (excluded from chart)
Harrow 91.67%
Influence Score
i
9.78% of network
(1.22)
Influence Breakdown
  • This Post (9.78%)
  • Harrow (11.96%)
  • Arnold Hills (9.78%)
  • Charles Theodore Williams (9.78%)
  • Harrow International School Appi (9.78%)
  • Harrow International School Beijing (9.78%)
  • Harrow International School Hong Kong (9.78%)
  • Harrow School Speech Room (9.78%)
  • Victor Pasmore (9.78%)
  • Walter Headlam (9.78%)
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 9 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 99 [Harrow] *
                            1 [Arnold Hills] *
                            1 [Charles Theodore Williams] *
                            1 [Harrow International School Appi] *
                            1 [Harrow International School Beijing] *
                            1 [Harrow International School Hong Kong] *
                            1 [Harrow School Speech Room] *
                            1 [Victor Pasmore] *
                            1 [Walter Headlam]
                           )

                         = 99

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1.22 [Harrow] *
                            1 [Arnold Hills] *
                            1 [Charles Theodore Williams] *
                            1 [Harrow International School Appi] *
                            1 [Harrow International School Beijing] *
                            1 [Harrow International School Hong Kong] *
                            1 [Harrow School Speech Room] *
                            1 [Victor Pasmore] *
                            1 [Walter Headlam]
                           )

                         = 1.22
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 9 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.93% (99 overall)
  • This Post (0.93%)
  • Arnold Hills (0.93%)
  • Charles Theodore Williams (0.93%)
  • Harrow International School Appi (0.93%)
  • Harrow International School Beijing (0.93%)
  • Harrow International School Hong Kong (0.93%)
  • Harrow School Speech Room (0.93%)
  • Victor Pasmore (0.93%)
  • Walter Headlam (0.93%)
Dominant nodes (excluded from chart)
Harrow 91.67%
Influence Share (vs Direct Neighbours)
9.78% (1.22 overall)
  • This Post (9.78%)
  • Harrow (11.96%)
  • Arnold Hills (9.78%)
  • Charles Theodore Williams (9.78%)
  • Harrow International School Appi (9.78%)
  • Harrow International School Beijing (9.78%)
  • Harrow International School Hong Kong (9.78%)
  • Harrow School Speech Room (9.78%)
  • Victor Pasmore (9.78%)
  • Walter Headlam (9.78%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Harrow ↗
Str: 99Inf: 1.22
Arnold Hills ↗
Str: 1Inf: 1
Charles Theodore Williams ↗
Str: 1Inf: 1
Harrow International School Appi ↗
Str: 1Inf: 1
Harrow International School Beijing ↗
Str: 1Inf: 1
Harrow International School Hong Kong ↗
Str: 1Inf: 1
Harrow School Speech Room ↗
Str: 1Inf: 1
Victor Pasmore ↗
Str: 1Inf: 1
Walter Headlam ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Walter Headlam ↗
Str: 1Inf: 1
Victor Pasmore ↗
Str: 1Inf: 1
Harrow School Speech Room ↗
Str: 1Inf: 1
Harrow International School Hong Kong ↗
Str: 1Inf: 1
Harrow International School Beijing ↗
Str: 1Inf: 1
Harrow International School Appi ↗
Str: 1Inf: 1
Charles Theodore Williams ↗
Str: 1Inf: 1
Arnold Hills ↗
Str: 1Inf: 1
Harrow ↗
Str: 99Inf: 1.22

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

Outbound Tags (1)
Harrow
Inbound Posts (1)
Harrow
Last calculated: Jul 3, 1:15 PM
London, England, United Kingdom32

Related Content

Figures

  • Walter Headlam
  • Arnold Hills
  • Charles Theodore Williams

Locations

  • Harrow
  • Harrow International School Beijing
  • Harrow International School Hong Kong

Topics

  • Harrow International School Appi
  • Harrow School Speech Room
  • Victor Pasmore