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Table 6 Feature importance in the node placement classifier and the size prediction regression model at k = 2 and k = 5, both for the Twitter CVE dataset

From: On the challenges of predicting microscopic dynamics of online conversations

Feature Node Size (k=2) Size (k=5)
Global
Current size 0.029
Depth 0.0 0.005
Root edges 0.0 0.11
Recent edges 0.0 0.0
Parent delay (mean, median) 0.0, 0.0 0.083, 0.082
Node
Node index 0.54
Node depth 0.28
Node parent delay 0.013
Subtree size 0.021
#Children 0.043
#Grandchildren 0.008
#Siblings 0.012
#Cousins 0.002
#Uncles 0.002
User (mean and median over conversations initiated by the user)
Max breadth 0, 0
Depth 0.003, 0.002
\(1{\text {st}}\) Breadth \(<10^{-3}\), 0
Lifetime 0, 0
Size \(<10^{-3}\), \(<10^{-3}\)
Root edges \(<10^{-3}\), \(<10^{-3}\)
Recent edges 0.011, 0.011
#Posts 0
Content (25 features, range given))
Root text 0–0.002 0–0.21 0–0.12
Temporal
Response time (mean, median) 0.02, 0.006 0.028, 0.009
\(1{\text {st}}\) Response time 0.43 0.028
Root time of day \(<10^{-3}\) 0.012 0.009
Root day of week 0 0.0 0.0