  A taocode is a kind of specially coded text-link on Taobao(the world's
biggest online shopping website), through which users can share messages about
products with each other. Analyzing taocodes can potentially facilitate
understanding of the social relationships between users and, more excitingly,
their online purchasing behaviors under the influence of taocode diffusion.
This paper innovatively investigates the problem of online purchasing
predictions from an information diffusion perspective, with taocode as a case
study. Specifically, we conduct profound observational studies on a large-scale
real-world dataset from Taobao, containing over 100M Taocode sharing records.
Inspired by our observations, we propose InfNet, a dynamic GNN-based framework
that models the information diffusion across Taocode. We then apply InfNet to
item purchasing predictions. Extensive experiments on real-world datasets
validate the effectiveness of InfNet compared with 8 state-of-the-art
baselines.
