Skip to main content

Table 5 Feature importance in the node placement classifier and the size prediction regression model at k = 2 and k = 5, both for the Reddit Crypto dataset. Reddit CVE feature importance is similar

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

Feature Node Size (k=2) Size (k=5)
Global
Current size 0.71
Depth 0 0
Root edges 0 0
Recent edges 0 0
Parent delay (mean, median) 0, 0 0.002, 0
Node
Node index 0.008
Node depth 0.015
Node parent delay 0.14 -
Subtree size 0.001
#Children 0.10
#Grandchildren 0.003
#Siblings 0.010
#Cousins \(<10^{-3}\)
#Uncles \(<10^{-3}\)
User (mean and median over conversations initiated by the user)
Max breadth \(<10^{-3}\), \(<10^{-3}\)
Depth \(<10^{-3}\), 0
\(1{\text {st}}\) Breadth \(<10^{-3}\), \(<10^{-3}\)
Lifetime 0, 0
Size \(<10^{-3}\), \(<10^{-3}\)
Root edges 0.001, \(<10^{-3}\)
Recent edges \(<10^{-3}\), \(<10^{-3}\)
#Posts 0
Content (25 features, range given)
Root text \(<10^{-3}\) \(<10^{-3}\) \(<10^{-3}\)
Temporal
Response time (mean, median) 0.28, 0.21 0.84, 0.04
\(1{\text {st}}\) Response time 0.50 0.11
Root time of day 0 0 0
Root day of week 0 0 0