Network Profile
View Network Math
Overall Strength
5.14%
of network (573.31M)
Direct Connections
6
Node & Network Strength Details
×
How is this calculated? The math continuously tracks how strongly this post is connected to the rest of the website.
Every tag forms a network link. The pie charts below show each connected post's base strength (PV) and influence (IV) as a share of this post's direct neighbourhood.
// 1. Base variables (minimum value of 1 to prevent zero-multiplication issues)
Outbound ($in) = max(1, 3) =
3
Inbound ($out) = max(1, 3) =
3
// 2. Node Base Values
Base Strength (PV) = $in × $out = 3 × 3 =
9
Base Influence (IV) = $in ÷ $out = 3 ÷ 3 =
1
// 3. Network Exponential Values (accumulating 9 direct neighbours)
Network Strength (CV) = Node PV × (Π Neighbour PVs) =
573.31M
Network Influence (TV) = Node IV × (Π Neighbour IVs) =
1.3333
Outbound
3
Tags on post
Inbound
3
Posts tagging this
Base Node Strength
9
Base Node Influence
1
Connected Nodes
9
Strength Share (vs Direct Neighbours)
This Post (5.14%) Kulm Wetland Management District (9.14%) North Dakota Highway 11 (9.14%) Postcards of Dickey County, North Dakota (5.14%) Sanborn Fire Insurance Map from Ellendale (2.29%) Fullerton, North Dakota (2.29%) Monango, North Dakota (2.29%) Ludden (2.29%) Forbes, North Dakota (0.57%)
Dominant nodes (excluded from chart) Dickey County 61.71%
Influence Share (vs Direct Neighbours)
This Post (9.68%) Dickey County (12.90%) Sanborn Fire Insurance Map from Ellendale (9.68%) Forbes, North Dakota (9.68%) Fullerton, North Dakota (9.68%) Kulm Wetland Management District (9.68%) Monango, North Dakota (9.68%) North Dakota Highway 11 (9.68%) Postcards of Dickey County, North Dakota (9.68%) Ludden (9.68%)
Connected Network (How neighbours affect this node)
Top Network Boosters (Highest Multipliers)
Weakest Connections (Lowest Multipliers)
Connection Health Audit (Red = broken 1-way link)
Last calculated math cycle: May 4, 11:39 PM
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Dickey County, United States
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