Network Profile
View Network Math
Overall Strength
< 0.01%
of network (1.66T)
Influence Score
28.40%
of network (55.434456)
Direct Connections
5
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 exactly which connected posts are generating the most power for this specific network cluster.
Outbound
3
Tags on post
Inbound
2
Posts tagging this
Base Node Strength
6
Base Node Influence
1.5
Connected Nodes
12
Network Strength Make-up
This Post (< 0.01%) CNN Newsroom (99.82%) Peter Daszak (0.13%) wuhan (0.05%) NIH (< 0.01%) EcoHealth Alliance (< 0.01%) Shi Zhengli (< 0.01%) Wuhan Institute of Virology (< 0.01%) Marion Koopmans (< 0.01%) Sars-Cov-2 (< 0.01%) Explained (< 0.01%) SARS-CoV-2 animations (< 0.01%) SARS-CoV-2 lifecycle (< 0.01%)
Influence Score Make-up
This Post (28.40%) CNN Newsroom (13.52%) EcoHealth Alliance (12.62%) NIH (6.31%) Sars-Cov-2 (6.15%) Marion Koopmans (4.73%) Shi Zhengli (4.73%) wuhan (4.73%) Wuhan Institute of Virology (4.73%) SARS-CoV-2 animations (4.61%) SARS-CoV-2 lifecycle (4.61%) Peter Daszak (4.51%) Explained (0.34%)
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: Apr 29, 1:12 PM
Close Report
Jiangxia District, Hubei, China
👁️ 30 Views
Analyzing Network Connections...
Most Relevant
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Depth: 1 Level
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