Modern sociology has profoundly uncovered many convincing social criteria for behavioral
analysis. Unfortunately, many of them are too subjective to be measured and very …

Influence Maximization (IM) is a classical combinatorial optimization problem, which can be
widely used in mobile networks, social computing, and recommendation systems. It aims at …

Aiming at selecting a small subset of nodes with maximum influence on networks, the
influence maximization (IM) problem has been extensively studied. Since it is# P-hard to …

Information diffusion prediction is an important task, which studies how information items
spread among users. With the success of deep learning techniques, recurrent neural …

Recent years have witnessed tremendous interest in understanding and predicting
information spread on social media platforms such as Twitter, Facebook, etc. Existing …

A central issue in rumor surveillance and management is decoding the complex dynamics of
rumor propagation, with an emphasis on predicting diffusion cascades. Recent studies focus …

Group buying, as an emerging form of purchase in social e-commerce websites, such as
Pinduoduo 1, has recently achieved great success. In this new business model, users …

Information diffusion prediction plays a crucial role in understanding the propagation of
information in social networks, encompassing both macroscopic and microscopic prediction …

The massive amounts of online user behavior data on social networks allow for the
investigation of information diffusion prediction, which is essential to comprehend how …

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 …