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Analyzing Network Connections...

Network Profile

Overall Strength
i
2.97% of network
(6.74 × 1025)
Strength Breakdown
  • This Post (2.97%)
  • Laura Linney (7.59%)
  • Tim Robbins (7.59%)
  • John Doman (5.81%)
  • Spencer Treat Clark (2.97%)
  • Michael Cerveris (2.97%)
  • Sean Penn (1.90%)
  • Cameron Bowen (1.90%)
  • Jonathan Togo (1.90%)
  • Brian McGrath (1.90%)
  • Elliot Cowan (1.90%)
  • Tom Guiry (1.07%)
  • Kevin Chapman (1.07%)
  • Emmy Rossum (1.07%)
  • Alexander (1.07%)
  • Adam Nelson (0.47%)
  • Jenny O'Hara (0.47%)
  • Stake Land (0.47%)
  • Andrew Mackin (0.12%)
  • Jason Kelly (0.12%)
  • Robert Wahlberg (0.12%)
  • Friend Request (0.12%)
  • World Trade Center (0.12%)
Dominant nodes (excluded from chart)
Mystic River 34.28%Laurence Fishburne 20.05%
Influence Score
i
4.00% of network
(1)
Influence Breakdown
  • This Post (4.00%)
  • Spencer Treat Clark (4.00%)
  • Sean Penn (4.00%)
  • Laurence Fishburne (4.00%)
  • Laura Linney (4.00%)
  • Tom Guiry (4.00%)
  • Tim Robbins (4.00%)
  • Mystic River (4.00%)
  • John Doman (4.00%)
  • Kevin Chapman (4.00%)
  • Adam Nelson (4.00%)
  • Andrew Mackin (4.00%)
  • Cameron Bowen (4.00%)
  • Emmy Rossum (4.00%)
  • Jason Kelly (4.00%)
  • Robert Wahlberg (4.00%)
  • Jonathan Togo (4.00%)
  • Jenny O'Hara (4.00%)
  • Brian McGrath (4.00%)
  • Elliot Cowan (4.00%)
  • Alexander (4.00%)
  • Stake Land (4.00%)
  • Friend Request (4.00%)
  • World Trade Center (4.00%)
  • Michael Cerveris (4.00%)
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 24 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 25 *
                           ( 25 [Spencer Treat Clark] *
                            16 [Sean Penn] *
                            169 [Laurence Fishburne] *
                            64 [Laura Linney] *
                            9 [Tom Guiry] *
                            64 [Tim Robbins] *
                            289 [Mystic River] *
                            49 [John Doman] *
                            9 [Kevin Chapman] *
                            4 [Adam Nelson] *
                            1 [Andrew Mackin] *
                            16 [Cameron Bowen] *
                            9 [Emmy Rossum] *
                            1 [Jason Kelly] *
                            1 [Robert Wahlberg] *
                            16 [Jonathan Togo] *
                            4 [Jenny O'Hara] *
                            16 [Brian McGrath] *
                            16 [Elliot Cowan] *
                            9 [Alexander] *
                            4 [Stake Land] *
                            1 [Friend Request] *
                            1 [World Trade Center] *
                            25 [Michael Cerveris]
                           )

                         = 6.74 x 10^25

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Spencer Treat Clark] *
                            1 [Sean Penn] *
                            1 [Laurence Fishburne] *
                            1 [Laura Linney] *
                            1 [Tom Guiry] *
                            1 [Tim Robbins] *
                            1 [Mystic River] *
                            1 [John Doman] *
                            1 [Kevin Chapman] *
                            1 [Adam Nelson] *
                            1 [Andrew Mackin] *
                            1 [Cameron Bowen] *
                            1 [Emmy Rossum] *
                            1 [Jason Kelly] *
                            1 [Robert Wahlberg] *
                            1 [Jonathan Togo] *
                            1 [Jenny O'Hara] *
                            1 [Brian McGrath] *
                            1 [Elliot Cowan] *
                            1 [Alexander] *
                            1 [Stake Land] *
                            1 [Friend Request] *
                            1 [World Trade Center] *
                            1 [Michael Cerveris]
                           )

                         = 1
Outbound 5 Tags on post
Inbound 5 Posts tagging this
Connections 24 Total nodes
Base Node Strength 25
Base Node Influence 1
Strength Share (vs Direct Neighbours)
2.97% (6.74 × 1025 overall)
  • This Post (2.97%)
  • Laura Linney (7.59%)
  • Tim Robbins (7.59%)
  • John Doman (5.81%)
  • Spencer Treat Clark (2.97%)
  • Michael Cerveris (2.97%)
  • Sean Penn (1.90%)
  • Cameron Bowen (1.90%)
  • Jonathan Togo (1.90%)
  • Brian McGrath (1.90%)
  • Elliot Cowan (1.90%)
  • Tom Guiry (1.07%)
  • Kevin Chapman (1.07%)
  • Emmy Rossum (1.07%)
  • Alexander (1.07%)
  • Adam Nelson (0.47%)
  • Jenny O'Hara (0.47%)
  • Stake Land (0.47%)
  • Andrew Mackin (0.12%)
  • Jason Kelly (0.12%)
  • Robert Wahlberg (0.12%)
  • Friend Request (0.12%)
  • World Trade Center (0.12%)
Dominant nodes (excluded from chart)
Mystic River 34.28%Laurence Fishburne 20.05%
Influence Share (vs Direct Neighbours)
4.00% (1 overall)
  • This Post (4.00%)
  • Spencer Treat Clark (4.00%)
  • Sean Penn (4.00%)
  • Laurence Fishburne (4.00%)
  • Laura Linney (4.00%)
  • Tom Guiry (4.00%)
  • Tim Robbins (4.00%)
  • Mystic River (4.00%)
  • John Doman (4.00%)
  • Kevin Chapman (4.00%)
  • Adam Nelson (4.00%)
  • Andrew Mackin (4.00%)
  • Cameron Bowen (4.00%)
  • Emmy Rossum (4.00%)
  • Jason Kelly (4.00%)
  • Robert Wahlberg (4.00%)
  • Jonathan Togo (4.00%)
  • Jenny O'Hara (4.00%)
  • Brian McGrath (4.00%)
  • Elliot Cowan (4.00%)
  • Alexander (4.00%)
  • Stake Land (4.00%)
  • Friend Request (4.00%)
  • World Trade Center (4.00%)
  • Michael Cerveris (4.00%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Spencer Treat Clark ↗
Str: 25Inf: 1
Sean Penn ↗
Str: 16Inf: 1
Laurence Fishburne ↗
Str: 169Inf: 1
Laura Linney ↗
Str: 64Inf: 1
Tom Guiry ↗
Str: 9Inf: 1
Tim Robbins ↗
Str: 64Inf: 1
Mystic River ↗
Str: 289Inf: 1
John Doman ↗
Str: 49Inf: 1
Kevin Chapman ↗
Str: 9Inf: 1
Adam Nelson ↗
Str: 4Inf: 1
Andrew Mackin ↗
Str: 1Inf: 1
Cameron Bowen ↗
Str: 16Inf: 1
Emmy Rossum ↗
Str: 9Inf: 1
Jason Kelly ↗
Str: 1Inf: 1
Robert Wahlberg ↗
Str: 1Inf: 1
Jonathan Togo ↗
Str: 16Inf: 1
Jenny O'Hara ↗
Str: 4Inf: 1
Brian McGrath ↗
Str: 16Inf: 1
Elliot Cowan ↗
Str: 16Inf: 1
Alexander ↗
Str: 9Inf: 1
Stake Land ↗
Str: 4Inf: 1
Friend Request ↗
Str: 1Inf: 1
World Trade Center ↗
Str: 1Inf: 1
Michael Cerveris ↗
Str: 25Inf: 1
Weakest Connections (Lowest Multipliers)
Michael Cerveris ↗
Str: 25Inf: 1
World Trade Center ↗
Str: 1Inf: 1
Friend Request ↗
Str: 1Inf: 1
Stake Land ↗
Str: 4Inf: 1
Alexander ↗
Str: 9Inf: 1
Elliot Cowan ↗
Str: 16Inf: 1
Brian McGrath ↗
Str: 16Inf: 1
Jenny O'Hara ↗
Str: 4Inf: 1
Jonathan Togo ↗
Str: 16Inf: 1
Robert Wahlberg ↗
Str: 1Inf: 1
Jason Kelly ↗
Str: 1Inf: 1
Emmy Rossum ↗
Str: 9Inf: 1
Cameron Bowen ↗
Str: 16Inf: 1
Andrew Mackin ↗
Str: 1Inf: 1
Adam Nelson ↗
Str: 4Inf: 1
Kevin Chapman ↗
Str: 9Inf: 1
John Doman ↗
Str: 49Inf: 1
Mystic River ↗
Str: 289Inf: 1
Tim Robbins ↗
Str: 64Inf: 1
Tom Guiry ↗
Str: 9Inf: 1
Laura Linney ↗
Str: 64Inf: 1
Laurence Fishburne ↗
Str: 169Inf: 1
Sean Penn ↗
Str: 16Inf: 1
Spencer Treat Clark ↗
Str: 25Inf: 1

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

Outbound Tags (5)
Alexander
Friend Request
Mystic River
Stake Land
World Trade Center
Inbound Posts (5)
Mystic River
Alexander
Stake Land
Friend Request
World Trade Center
Last calculated: Jul 4, 9:56 AM
23

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Actors

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  • Kevin Chapman
  • Jenny O'Hara
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Films

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