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Analyzing Network Connections...

Network Profile

Overall Strength
i
0.65% of network
(9.54 × 1038)
Strength Breakdown
  • This Post (0.65%)
  • Law & Order (9.40%)
  • The Munsters (9.40%)
  • Zelig (9.40%)
  • Kinsey (8.43%)
  • My Cousin Vinny (8.43%)
  • King Richard (8.43%)
  • Water for Elephants (8.43%)
  • St. Elsewhere (8.43%)
  • One Day at a Time (8.43%)
  • Edward Scissorhands (7.52%)
  • The Blacklist (7.52%)
  • The X-Files (2.34%)
  • Susan Blommaert (0.94%)
  • Kavi Raz (0.65%)
  • Mary Louise Wilson (0.52%)
  • Fred Gwynne (0.42%)
  • Car 54, Where Are You? (0.23%)
  • Brad Greenquist (0.23%)
  • She-Devil (0.10%)
  • Among Us (0.03%)
  • The Black Prince (0.03%)
  • The Gold Bracelet (0.03%)
Influence Score
i
4.28% of network
(1.39)
Influence Breakdown
  • This Post (4.28%)
  • Mary Louise Wilson (5.35%)
  • The X-Files (4.76%)
  • Edward Scissorhands (4.28%)
  • Susan Blommaert (4.28%)
  • Kinsey (4.28%)
  • The Blacklist (4.28%)
  • Law & Order (4.28%)
  • My Cousin Vinny (4.28%)
  • Fred Gwynne (4.28%)
  • Car 54, Where Are You? (4.28%)
  • The Munsters (4.28%)
  • King Richard (4.28%)
  • Brad Greenquist (4.28%)
  • Water for Elephants (4.28%)
  • Kavi Raz (4.28%)
  • St. Elsewhere (4.28%)
  • Among Us (4.28%)
  • The Black Prince (4.28%)
  • The Gold Bracelet (4.28%)
  • One Day at a Time (4.28%)
  • Zelig (4.28%)
  • She-Devil (4.28%)
Direct Connections 10

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, 5) = 5
$outbound = max(1, 5) = 5

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 5 * 5 = 25
Base_Influence (IV) = $inbound / $outbound = 5 / 5 = 1

// 3. Exponential Network Values (accumulating 22 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 25 *
                           ( 20 [Mary Louise Wilson] *
                            90 [The X-Files] *
                            289 [Edward Scissorhands] *
                            36 [Susan Blommaert] *
                            324 [Kinsey] *
                            289 [The Blacklist] *
                            361 [Law & Order] *
                            324 [My Cousin Vinny] *
                            16 [Fred Gwynne] *
                            9 [Car 54, Where Are You?] *
                            361 [The Munsters] *
                            324 [King Richard] *
                            9 [Brad Greenquist] *
                            324 [Water for Elephants] *
                            25 [Kavi Raz] *
                            324 [St. Elsewhere] *
                            1 [Among Us] *
                            1 [The Black Prince] *
                            1 [The Gold Bracelet] *
                            324 [One Day at a Time] *
                            361 [Zelig] *
                            4 [She-Devil]
                           )

                         = 9.54 x 10^38

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1.25 [Mary Louise Wilson] *
                            1.11 [The X-Files] *
                            1 [Edward Scissorhands] *
                            1 [Susan Blommaert] *
                            1 [Kinsey] *
                            1 [The Blacklist] *
                            1 [Law & Order] *
                            1 [My Cousin Vinny] *
                            1 [Fred Gwynne] *
                            1 [Car 54, Where Are You?] *
                            1 [The Munsters] *
                            1 [King Richard] *
                            1 [Brad Greenquist] *
                            1 [Water for Elephants] *
                            1 [Kavi Raz] *
                            1 [St. Elsewhere] *
                            1 [Among Us] *
                            1 [The Black Prince] *
                            1 [The Gold Bracelet] *
                            1 [One Day at a Time] *
                            1 [Zelig] *
                            1 [She-Devil]
                           )

                         = 1.39
Outbound 5 Tags on post
Inbound 5 Posts tagging this
Connections 22 Total nodes
Base Node Strength 25
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.65% (9.54 × 1038 overall)
  • This Post (0.65%)
  • Law & Order (9.40%)
  • The Munsters (9.40%)
  • Zelig (9.40%)
  • Kinsey (8.43%)
  • My Cousin Vinny (8.43%)
  • King Richard (8.43%)
  • Water for Elephants (8.43%)
  • St. Elsewhere (8.43%)
  • One Day at a Time (8.43%)
  • Edward Scissorhands (7.52%)
  • The Blacklist (7.52%)
  • The X-Files (2.34%)
  • Susan Blommaert (0.94%)
  • Kavi Raz (0.65%)
  • Mary Louise Wilson (0.52%)
  • Fred Gwynne (0.42%)
  • Car 54, Where Are You? (0.23%)
  • Brad Greenquist (0.23%)
  • She-Devil (0.10%)
  • Among Us (0.03%)
  • The Black Prince (0.03%)
  • The Gold Bracelet (0.03%)
Influence Share (vs Direct Neighbours)
4.28% (1.39 overall)
  • This Post (4.28%)
  • Mary Louise Wilson (5.35%)
  • The X-Files (4.76%)
  • Edward Scissorhands (4.28%)
  • Susan Blommaert (4.28%)
  • Kinsey (4.28%)
  • The Blacklist (4.28%)
  • Law & Order (4.28%)
  • My Cousin Vinny (4.28%)
  • Fred Gwynne (4.28%)
  • Car 54, Where Are You? (4.28%)
  • The Munsters (4.28%)
  • King Richard (4.28%)
  • Brad Greenquist (4.28%)
  • Water for Elephants (4.28%)
  • Kavi Raz (4.28%)
  • St. Elsewhere (4.28%)
  • Among Us (4.28%)
  • The Black Prince (4.28%)
  • The Gold Bracelet (4.28%)
  • One Day at a Time (4.28%)
  • Zelig (4.28%)
  • She-Devil (4.28%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Mary Louise Wilson ↗
Str: 20Inf: 1.25
The X-Files ↗
Str: 90Inf: 1.11
Edward Scissorhands ↗
Str: 289Inf: 1
Susan Blommaert ↗
Str: 36Inf: 1
Kinsey ↗
Str: 324Inf: 1
The Blacklist ↗
Str: 289Inf: 1
Law & Order ↗
Str: 361Inf: 1
My Cousin Vinny ↗
Str: 324Inf: 1
Fred Gwynne ↗
Str: 16Inf: 1
Car 54, Where Are You? ↗
Str: 9Inf: 1
The Munsters ↗
Str: 361Inf: 1
King Richard ↗
Str: 324Inf: 1
Brad Greenquist ↗
Str: 9Inf: 1
Water for Elephants ↗
Str: 324Inf: 1
Kavi Raz ↗
Str: 25Inf: 1
St. Elsewhere ↗
Str: 324Inf: 1
Among Us ↗
Str: 1Inf: 1
The Black Prince ↗
Str: 1Inf: 1
The Gold Bracelet ↗
Str: 1Inf: 1
One Day at a Time ↗
Str: 324Inf: 1
Zelig ↗
Str: 361Inf: 1
She-Devil ↗
Str: 4Inf: 1
Weakest Connections (Lowest Multipliers)
She-Devil ↗
Str: 4Inf: 1
Zelig ↗
Str: 361Inf: 1
One Day at a Time ↗
Str: 324Inf: 1
The Gold Bracelet ↗
Str: 1Inf: 1
The Black Prince ↗
Str: 1Inf: 1
Among Us ↗
Str: 1Inf: 1
St. Elsewhere ↗
Str: 324Inf: 1
Kavi Raz ↗
Str: 25Inf: 1
Water for Elephants ↗
Str: 324Inf: 1
Brad Greenquist ↗
Str: 9Inf: 1
King Richard ↗
Str: 324Inf: 1
The Munsters ↗
Str: 361Inf: 1
Car 54, Where Are You? ↗
Str: 9Inf: 1
Fred Gwynne ↗
Str: 16Inf: 1
My Cousin Vinny ↗
Str: 324Inf: 1
Law & Order ↗
Str: 361Inf: 1
The Blacklist ↗
Str: 289Inf: 1
Kinsey ↗
Str: 324Inf: 1
Susan Blommaert ↗
Str: 36Inf: 1
Edward Scissorhands ↗
Str: 289Inf: 1
The X-Files ↗
Str: 90Inf: 1.11
Mary Louise Wilson ↗
Str: 20Inf: 1.25

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

Outbound Tags (5)
Brad Greenquist
Fred Gwynne
Kavi Raz
Mary Louise Wilson
Susan Blommaert
Inbound Posts (5)
Susan Blommaert
Fred Gwynne
Brad Greenquist
Kavi Raz
Mary Louise Wilson
Last calculated: Nov 11, 9:44 AM
45

Related Content

Actors

  • Mary Louise Wilson
  • Fred Gwynne
  • Susan Blommaert
  • Brad Greenquist
  • Kavi Raz

Films

  • My Cousin Vinny
  • St. Elsewhere
  • Edward Scissorhands
  • Among Us
  • The Munsters
  • The Black Prince
  • Kinsey
  • King Richard
  • The Gold Bracelet
  • The X-Files
  • One Day at a Time
  • The Blacklist
  • Water for Elephants
  • Zelig
  • Law & Order
  • She-Devil

Topics

  • Car 54, Where Are You?

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