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Analyzing Network Connections...

Network Profile

Overall Strength
i
0.21% of network
(931.99T)
Strength Breakdown
  • This Post (0.21%)
  • Michael Beach (7.39%)
  • Bobby Cannavale (7.39%)
  • Amy Carlson (5.13%)
  • Skipp Sudduth (5.13%)
  • Joe Lisi (3.29%)
  • Leila Danette (3.29%)
  • Kim Raver (2.46%)
  • Chris Bauer (1.85%)
  • Eddie Cibrian (1.85%)
  • Nia Long (0.82%)
  • Bill Walsh (0.82%)
  • Bonnie Dennison (0.21%)
  • Coby Bell (0.21%)
  • Jason Wiles (0.21%)
  • Saundra McClain (0.21%)
  • Tia Texada (0.21%)
Dominant nodes (excluded from chart)
Third Watch 59.34%
Influence Score
i
5.45% of network
(1.33)
Influence Breakdown
  • This Post (5.45%)
  • Kim Raver (7.27%)
  • Michael Beach (5.45%)
  • Bobby Cannavale (5.45%)
  • Chris Bauer (5.45%)
  • Joe Lisi (5.45%)
  • Amy Carlson (5.45%)
  • Nia Long (5.45%)
  • Eddie Cibrian (5.45%)
  • Skipp Sudduth (5.45%)
  • Leila Danette (5.45%)
  • Third Watch (5.45%)
  • Bill Walsh (5.45%)
  • Bonnie Dennison (5.45%)
  • Coby Bell (5.45%)
  • Jason Wiles (5.45%)
  • Saundra McClain (5.45%)
  • Tia Texada (5.45%)
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 17 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 12 [Kim Raver] *
                            36 [Michael Beach] *
                            36 [Bobby Cannavale] *
                            9 [Chris Bauer] *
                            16 [Joe Lisi] *
                            25 [Amy Carlson] *
                            4 [Nia Long] *
                            9 [Eddie Cibrian] *
                            25 [Skipp Sudduth] *
                            16 [Leila Danette] *
                            289 [Third Watch] *
                            4 [Bill Walsh] *
                            1 [Bonnie Dennison] *
                            1 [Coby Bell] *
                            1 [Jason Wiles] *
                            1 [Saundra McClain] *
                            1 [Tia Texada]
                           )

                         = 931.99T

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1.33 [Kim Raver] *
                            1 [Michael Beach] *
                            1 [Bobby Cannavale] *
                            1 [Chris Bauer] *
                            1 [Joe Lisi] *
                            1 [Amy Carlson] *
                            1 [Nia Long] *
                            1 [Eddie Cibrian] *
                            1 [Skipp Sudduth] *
                            1 [Leila Danette] *
                            1 [Third Watch] *
                            1 [Bill Walsh] *
                            1 [Bonnie Dennison] *
                            1 [Coby Bell] *
                            1 [Jason Wiles] *
                            1 [Saundra McClain] *
                            1 [Tia Texada]
                           )

                         = 1.33
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 17 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
0.21% (931.99T overall)
  • This Post (0.21%)
  • Michael Beach (7.39%)
  • Bobby Cannavale (7.39%)
  • Amy Carlson (5.13%)
  • Skipp Sudduth (5.13%)
  • Joe Lisi (3.29%)
  • Leila Danette (3.29%)
  • Kim Raver (2.46%)
  • Chris Bauer (1.85%)
  • Eddie Cibrian (1.85%)
  • Nia Long (0.82%)
  • Bill Walsh (0.82%)
  • Bonnie Dennison (0.21%)
  • Coby Bell (0.21%)
  • Jason Wiles (0.21%)
  • Saundra McClain (0.21%)
  • Tia Texada (0.21%)
Dominant nodes (excluded from chart)
Third Watch 59.34%
Influence Share (vs Direct Neighbours)
5.45% (1.33 overall)
  • This Post (5.45%)
  • Kim Raver (7.27%)
  • Michael Beach (5.45%)
  • Bobby Cannavale (5.45%)
  • Chris Bauer (5.45%)
  • Joe Lisi (5.45%)
  • Amy Carlson (5.45%)
  • Nia Long (5.45%)
  • Eddie Cibrian (5.45%)
  • Skipp Sudduth (5.45%)
  • Leila Danette (5.45%)
  • Third Watch (5.45%)
  • Bill Walsh (5.45%)
  • Bonnie Dennison (5.45%)
  • Coby Bell (5.45%)
  • Jason Wiles (5.45%)
  • Saundra McClain (5.45%)
  • Tia Texada (5.45%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Kim Raver ↗
Str: 12Inf: 1.33
Michael Beach ↗
Str: 36Inf: 1
Bobby Cannavale ↗
Str: 36Inf: 1
Chris Bauer ↗
Str: 9Inf: 1
Joe Lisi ↗
Str: 16Inf: 1
Amy Carlson ↗
Str: 25Inf: 1
Nia Long ↗
Str: 4Inf: 1
Eddie Cibrian ↗
Str: 9Inf: 1
Skipp Sudduth ↗
Str: 25Inf: 1
Leila Danette ↗
Str: 16Inf: 1
Third Watch ↗
Str: 289Inf: 1
Bill Walsh ↗
Str: 4Inf: 1
Bonnie Dennison ↗
Str: 1Inf: 1
Coby Bell ↗
Str: 1Inf: 1
Jason Wiles ↗
Str: 1Inf: 1
Saundra McClain ↗
Str: 1Inf: 1
Tia Texada ↗
Str: 1Inf: 1
Weakest Connections (Lowest Multipliers)
Tia Texada ↗
Str: 1Inf: 1
Saundra McClain ↗
Str: 1Inf: 1
Jason Wiles ↗
Str: 1Inf: 1
Coby Bell ↗
Str: 1Inf: 1
Bonnie Dennison ↗
Str: 1Inf: 1
Bill Walsh ↗
Str: 4Inf: 1
Third Watch ↗
Str: 289Inf: 1
Leila Danette ↗
Str: 16Inf: 1
Skipp Sudduth ↗
Str: 25Inf: 1
Eddie Cibrian ↗
Str: 9Inf: 1
Nia Long ↗
Str: 4Inf: 1
Amy Carlson ↗
Str: 25Inf: 1
Joe Lisi ↗
Str: 16Inf: 1
Chris Bauer ↗
Str: 9Inf: 1
Bobby Cannavale ↗
Str: 36Inf: 1
Michael Beach ↗
Str: 36Inf: 1
Kim Raver ↗
Str: 12Inf: 1.33

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

Outbound Tags (1)
Third Watch
Inbound Posts (1)
Third Watch
Last calculated: Jun 9, 4:22 AM
24

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Actors

  • Chris Bauer
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  • Saundra McClain
  • Michael Beach
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