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, 3) = 3
$outbound = max(1, 2) = 2
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 3 * 2 = 6
Base_Influence (IV) = $inbound / $outbound = 3 / 2 = 1.5
// 3. Exponential Network Values (accumulating 38 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 6 *
( 50 [Beijing] *
6 [Western China] *
6 [Phill Niblock] *
12 [Dubai] *
143 [Taiwan] *
342 [United Arab Emirates] *
1 [Abu Dhabi] *
1 [Ajman] *
1 [Fujairah] *
1 [Ras Al Khaimah] *
1 [Sharjah] *
1 [Umm Al Quwain] *
1 [Zhytomyr] *
1 [Al Bithnah] *
1 [Emirates Mars missions] *
1 [Gallery pages of the United Arab Emirates] *
1 [Information in the United Arab Emirates] *
1 [Society of the United Arab Emirates] *
1 [United Arab Emirates by media type] *
1 [Wikimedia movement in the United Arab Emirates] *
1 [Wikivoyage banners of the United Arab Emirates] *
1 [الإمارات العربية المتحدة / United Arab Emirates] *
4 [Central China] *
1 [East China] *
1 [North China] *
1 [Northeast China] *
1 [South China] *
4 [Fujian Province] *
4 [KaohsiungCity] *
4 [New Taipei City] *
4 [TaichungCity] *
4 [TainanCity] *
4 [TaipeiCity] *
4 [Taiwan Province] *
4 [Taoyuan City] *
1 [Cauliflower in the Philippines] *
1 [Society of the Philippines] *
306 [China]
)
= 5.08 x 10^17
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1.5 *
( 2 [Beijing] *
1.5 [Western China] *
1.5 [Phill Niblock] *
1.33 [Dubai] *
1.18 [Taiwan] *
1.06 [United Arab Emirates] *
1 [Abu Dhabi] *
1 [Ajman] *
1 [Fujairah] *
1 [Ras Al Khaimah] *
1 [Sharjah] *
1 [Umm Al Quwain] *
1 [Zhytomyr] *
1 [Al Bithnah] *
1 [Emirates Mars missions] *
1 [Gallery pages of the United Arab Emirates] *
1 [Information in the United Arab Emirates] *
1 [Society of the United Arab Emirates] *
1 [United Arab Emirates by media type] *
1 [Wikimedia movement in the United Arab Emirates] *
1 [Wikivoyage banners of the United Arab Emirates] *
1 [الإمارات العربية المتحدة / United Arab Emirates] *
1 [Central China] *
1 [East China] *
1 [North China] *
1 [Northeast China] *
1 [South China] *
1 [Fujian Province] *
1 [KaohsiungCity] *
1 [New Taipei City] *
1 [TaichungCity] *
1 [TainanCity] *
1 [TaipeiCity] *
1 [Taiwan Province] *
1 [Taoyuan City] *
1 [Cauliflower in the Philippines] *
1 [Society of the Philippines] *
0.9444 [China]
)
= 10.6
Outbound
3
Tags on post
Inbound
2
Posts tagging this
Connections
38
Total nodes
Base Node Strength
6
Base Node Influence
1.5
Strength Share (vs Direct Neighbours)
0.65%
(5.08 × 1017 overall)
Dominant nodes (excluded from chart)United Arab Emirates 36.81%China 32.94%Taiwan 15.39%Beijing 5.38%Dubai 1.29%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
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Connection Health Audit (Red = broken 1-way link)