Muso

Directory About
Continue with Google
Continue with with Facebook

Top Related Posts

St. Josef am SeeChurch of St. Josef am See

Recent Logins

View Members Directory

Tadhg Kelleher
Last login: 2 hours ago
Comments: 0

jacierlogyn
Last login: 4 days ago
Comments: 0

Eileen Lally
Last login: 4 weeks ago
Comments: 0

Özkan Konu
Last login: 1 month ago
Comments: 0

Anne Marie Bevan
Last login: 2 months ago
Comments: 0

Kevin Greene
Last login: 2 months ago
Comments: 0

Church of St. Josef am See - Interior

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
3.33% of network
(100)
Strength Breakdown
  • This Post (3.33%)
  • St. Josef am See (83.33%)
  • Church of St. Josef am See (13.33%)
Influence Score
i
33.33% of network
(1)
Influence Breakdown
  • This Post (33.33%)
  • St. Josef am See (33.33%)
  • Church of St. Josef am See (33.33%)
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 2 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
                         = 1 *
                           ( 25 [St. Josef am See] *
                            4 [Church of St. Josef am See]
                           )

                         = 100

Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
                         = 1 *
                           ( 1 [St. Josef am See] *
                            1 [Church of St. Josef am See]
                           )

                         = 1
Outbound 1 Tags on post
Inbound 1 Posts tagging this
Connections 2 Total nodes
Base Node Strength 1
Base Node Influence 1
Strength Share (vs Direct Neighbours)
3.33% (100 overall)
  • This Post (3.33%)
  • St. Josef am See (83.33%)
  • Church of St. Josef am See (13.33%)
Influence Share (vs Direct Neighbours)
33.33% (1 overall)
  • This Post (33.33%)
  • St. Josef am See (33.33%)
  • Church of St. Josef am See (33.33%)

Connected Network Hierarchy

Sort list by:
Top Network Boosters (Highest Multipliers)
St. Josef am See ↗
Str: 25Inf: 1
Church of St. Josef am See ↗
Str: 4Inf: 1
Weakest Connections (Lowest Multipliers)
Church of St. Josef am See ↗
Str: 4Inf: 1
St. Josef am See ↗
Str: 25Inf: 1

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

Outbound Tags (1)
Church of St. Josef am See
Inbound Posts (1)
Church of St. Josef am See
Last calculated: Jul 2, 9:55 PM
20

Related Content

Locations

  • St. Josef am See

Topics

  • Church of St. Josef am See