Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

Leehom Wang
BlackhatDanny Burstein

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 10 hours ago
Comments: 0

Eileen Lally
Last login: 2 weeks ago
Comments: 0

Özkan Konu
Last login: 1 month ago
Comments: 0

Anne Marie Bevan
Last login: 1 month ago
Comments: 0

Kevin Greene
Last login: 1 month ago
Comments: 0

Seán Millar
Last login: 1 month ago
Comments: 0

Blackhat panel at the 2014 Comic-Con International

Loading Graph...
Press Spacebar to toggle layout
Join the conversation

💬 Know something?

Sign in to leave a note, add a photo, or make a connection.

Continue with Google Continue with Facebook

Keep Muso free

Muso is built by one person, for the love of it. no investors — just your support.

€10
Covers an hour of research
Most popular
€25
Keeps the archive running
€50
Funds a full week of work
✎ Enter my own amount
€5
per month · cancel any time

You'll confirm the amount on the next screen

Donate €25 →
Secure checkout via Stripe  ·  No account needed

Analyzing Network Connections...

Network Profile

Overall Strength
i
3.57% of network
(648)
Strength Breakdown
  • This Post (3.57%)
  • Danny Burstein (42.86%)
  • Leehom Wang (32.14%)
  • Blackhat (21.43%)
Influence Score
i
25.00% of network
(0.8889)
Influence Breakdown
  • This Post (25.00%)
  • Danny Burstein (33.33%)
  • Leehom Wang (25.00%)
  • Blackhat (16.67%)
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 3 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 12 [Danny Burstein] *
                            9 [Leehom Wang] *
                            6 [Blackhat]
                           )

                         = 648

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1.33 [Danny Burstein] *
                            1 [Leehom Wang] *
                            0.6667 [Blackhat]
                           )

                         = 0.8889
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 3 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
3.57% (648 overall)
  • This Post (3.57%)
  • Danny Burstein (42.86%)
  • Leehom Wang (32.14%)
  • Blackhat (21.43%)
Influence Share (vs Direct Neighbours)
25.00% (0.8889 overall)
  • This Post (25.00%)
  • Danny Burstein (33.33%)
  • Leehom Wang (25.00%)
  • Blackhat (16.67%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Danny Burstein ↗
Str: 12Inf: 1.33
Leehom Wang ↗
Str: 9Inf: 1
Blackhat ↗
Str: 6Inf: 0.6667
Weakest Connections (Lowest Multipliers)
Blackhat ↗
Str: 6Inf: 0.6667
Leehom Wang ↗
Str: 9Inf: 1
Danny Burstein ↗
Str: 12Inf: 1.33

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

Outbound Tags (1)
Blackhat
Inbound Posts (1)
Blackhat
Last calculated: Jun 23, 3:55 PM
50

Related Content

Actors

  • Danny Burstein

Figures

  • Leehom Wang

Topics

  • Blackhat