In this paper, we study an important yet largely under-explored setting of graph embedding,
ie, embedding communities instead of each individual nodes. We find that community …

In this paper, we focus on information diffusion through social networks. Based on the well-
known Independent Cascade model, we embed users of the social network in a latent space …

In this paper, we introduce a new setting for graph embedding, which considers embedding
communities instead of individual nodes. We find that community embedding is not only …

Online debate forums provide a valuable resource for textual discussions about
controversial social and political issues. Discovering the viewpoints and their discourse or …

Most existing community-related studies focus on detection, which aim to find the community
membership for each user from user friendship links. However, membership alone, without a …

Social media platforms such as weblogs and social networking sites provide Internet users
with an unprecedented means to express their opinions and debate on a wide range of …

The study of community detection in networks has drawn great attention in recent years. To
find communities and to understand community semantics, both network topology and …

The role of the Web in political exchange has been crucial for society. Its platforms have
connected people and allowed manifestation, organization, and access to information; …

The Web has evolved to a dominant platform where everyone has the opportunity to express
their opinions, to interact with other users, and to debate on emerging events happening …

Signed link prediction in social networks aims to reveal the underlying relationships (ie,
links) among users (ie, nodes) given their existing positive and negative interactions …