Automatic response forecasting for news media plays a crucial role in enabling content
producers to efficiently predict the impact of news releases and prevent unexpected …

Network embedding plays an important role in a variety of social network applications.
Existing network embedding methods, explicitly or implicitly, can be categorized into …

This paper investigates the few-shot temporal reasoning capability within the hyperbolic
space. The goal is to forecast future events for newly emerging entities within temporal …

This paper studies speculative reasoning task on real-world knowledge graphs (KG) that
contain both\textit {false negative issue}(ie, potential true facts being excluded) and\textit …

This paper addresses influence pathway discovery, a key emerging problem in today's
online media. We propose a discovery algorithm that leverages recently published work on …

Network alignment is the task of establishing one-to-one correspondences between the
nodes of different graphs and finds a plethora of applications in high-impact domains …

The paper advances belief representation learning in polarized networks–the mapping of
social beliefs espoused by users and posts in a polarized network into a disentangled latent …

This paper investigates cross-lingual temporal knowledge graph reasoning problem, which
aims to facilitate reasoning on Temporal Knowledge Graphs (TKGs) in low-resource …

Short text clustering is challenging since it takes imbalanced and noisy data as inputs.
Existing approaches cannot solve this problem well, since (1) they are prone to obtain …

The proliferation of political memes in modern information campaigns calls for efficient
solutions for image classification by ideological affiliation. While significant advances have …