  Much effort has been devoted to understand how temporal network features and
the choice of the source node affect the prevalence of a diffusion process. In
this work, we addressed the further question: node pairs with what kind of
local and temporal connection features tend to appear in a diffusion trajectory
or path, thus contribute to the actual information diffusion. We consider the
Susceptible-Infected spreading process with a given infection probability per
contact on a large number of real-world temporal networks. We illustrate how to
construct the information diffusion backbone where the weight of each link
tells the probability that a node pair appears in a diffusion process starting
from a random node. We unravel how these backbones corresponding to different
infection probabilities relate to each other and point out the importance of
two extreme backbones: the backbone with infection probability one and the
integrated network, between which other backbones vary. We find that the
temporal node pair feature that we proposed could better predict the links in
the extreme backbone with infection probability one as well as the high weight
links than the features derived from the integrated network. This universal
finding across all the empirical networks highlights that temporal information
are crucial in determining a node pair's role in a diffusion process. A node
pair with many early contacts tends to appear in a diffusion process. Our
findings shed lights on the in-depth understanding and may inspire the control
of information spread.
