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Johns Hopkins University
Colin McPhee
Peabody InstituteGeorge Peabody (1792-1869)Michael McKinley SillermanGustav StrubeHarold RandolphDuncan S. JohnsonJoseph SilkJessica Williams

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Johns Hopkins

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Related Images

Johns Hopkins Blue Jays
Faculty of Peabody Institute
Johns Hopkins Inlet
John Huston Finley
Sheridan Libraries
Johns Hopkins University athletics
Applied Physics Laboratory
John W. Garrett

Connected Musicians

  • Gustav Strube
  • Harold Randolph
  • Michael McKinley Sillerman

Analyzing Network Connections...

Loading Map...

Nearest Locations

  • Thumbnail for Johns Hopkins University
    Johns Hopkins University0.0 km away
  • 📍
    Birdland0.0 km away
  • 📍
    Peabody Institute0.0 km away
  • 📍
    Dark Aether Project0.1 km away
  • 📍
    Historics0.6 km away

Network Profile

Overall Strength
i
4.69% of network
(210.45B)
Strength Breakdown
  • This Post (4.69%)
  • Peabody Institute (18.77%)
  • Gustav Strube (4.69%)
  • Johns Hopkins University (4.69%)
  • Jessica Williams (4.69%)
  • Harold Randolph (1.17%)
  • Michael McKinley Sillerman (1.17%)
  • Duncan S. Johnson (1.17%)
  • Joseph Silk (1.17%)
  • George Peabody (1792-1869) (0.29%)
Dominant nodes (excluded from chart)
Colin McPhee 57.48%
Influence Score
i
9.09% of network
(1)
Influence Breakdown
  • This Post (9.09%)
  • Colin McPhee (9.09%)
  • George Peabody (1792-1869) (9.09%)
  • Peabody Institute (9.09%)
  • Gustav Strube (9.09%)
  • Harold Randolph (9.09%)
  • Michael McKinley Sillerman (9.09%)
  • Johns Hopkins University (9.09%)
  • Jessica Williams (9.09%)
  • Duncan S. Johnson (9.09%)
  • Joseph Silk (9.09%)
Direct Connections 8

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, 4) = 4
$outbound = max(1, 4) = 4

// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 4 * 4 = 16
Base_Influence (IV) = $inbound / $outbound = 4 / 4 = 1

// 3. Exponential Network Values (accumulating 10 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 16 *
                           ( 196 [Colin McPhee] *
                            1 [George Peabody (1792-1869)] *
                            64 [Peabody Institute] *
                            16 [Gustav Strube] *
                            4 [Harold Randolph] *
                            4 [Michael McKinley Sillerman] *
                            16 [Johns Hopkins University] *
                            16 [Jessica Williams] *
                            4 [Duncan S. Johnson] *
                            4 [Joseph Silk]
                           )

                         = 210.45B

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [Colin McPhee] *
                            1 [George Peabody (1792-1869)] *
                            1 [Peabody Institute] *
                            1 [Gustav Strube] *
                            1 [Harold Randolph] *
                            1 [Michael McKinley Sillerman] *
                            1 [Johns Hopkins University] *
                            1 [Jessica Williams] *
                            1 [Duncan S. Johnson] *
                            1 [Joseph Silk]
                           )

                         = 1
Outbound 4 Tags on post
Inbound 4 Posts tagging this
Connections 10 Total nodes
Base Node Strength 16
Base Node Influence 1
Strength Share (vs Direct Neighbours)
4.69% (210.45B overall)
  • This Post (4.69%)
  • Peabody Institute (18.77%)
  • Gustav Strube (4.69%)
  • Johns Hopkins University (4.69%)
  • Jessica Williams (4.69%)
  • Harold Randolph (1.17%)
  • Michael McKinley Sillerman (1.17%)
  • Duncan S. Johnson (1.17%)
  • Joseph Silk (1.17%)
  • George Peabody (1792-1869) (0.29%)
Dominant nodes (excluded from chart)
Colin McPhee 57.48%
Influence Share (vs Direct Neighbours)
9.09% (1 overall)
  • This Post (9.09%)
  • Colin McPhee (9.09%)
  • George Peabody (1792-1869) (9.09%)
  • Peabody Institute (9.09%)
  • Gustav Strube (9.09%)
  • Harold Randolph (9.09%)
  • Michael McKinley Sillerman (9.09%)
  • Johns Hopkins University (9.09%)
  • Jessica Williams (9.09%)
  • Duncan S. Johnson (9.09%)
  • Joseph Silk (9.09%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
Colin McPhee ↗
Str: 196Inf: 1
George Peabody (1792-1869) ↗
Str: 1Inf: 1
Peabody Institute ↗
Str: 64Inf: 1
Gustav Strube ↗
Str: 16Inf: 1
Harold Randolph ↗
Str: 4Inf: 1
Michael McKinley Sillerman ↗
Str: 4Inf: 1
Johns Hopkins University ↗
Str: 16Inf: 1
Jessica Williams ↗
Str: 16Inf: 1
Duncan S. Johnson ↗
Str: 4Inf: 1
Joseph Silk ↗
Str: 4Inf: 1
Weakest Connections (Lowest Multipliers)
Joseph Silk ↗
Str: 4Inf: 1
Duncan S. Johnson ↗
Str: 4Inf: 1
Jessica Williams ↗
Str: 16Inf: 1
Johns Hopkins University ↗
Str: 16Inf: 1
Michael McKinley Sillerman ↗
Str: 4Inf: 1
Harold Randolph ↗
Str: 4Inf: 1
Gustav Strube ↗
Str: 16Inf: 1
Peabody Institute ↗
Str: 64Inf: 1
George Peabody (1792-1869) ↗
Str: 1Inf: 1
Colin McPhee ↗
Str: 196Inf: 1

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

Outbound Tags (4)
Duncan S. Johnson
Johns Hopkins University
Joseph Silk
peabody institute
Inbound Posts (4)
Peabody Institute
Johns Hopkins University
Duncan S. Johnson
Joseph Silk
Last calculated: Jul 25, 8:36 AM
Baltimore, Maryland, United States70

Related Content

Actors

  • Jessica Williams

Composers

  • Colin McPhee
  • George Peabody (1792-1869)

Educations

  • Peabody Institute
  • Johns Hopkins University

Figures

  • Duncan S. Johnson
  • Joseph Silk