Online social networks have become a fundamental part of the global online experience.
They facilitate different modes of communication and social interactions, enabling …

Rapid advancements in internet and social media technologies have made “information
overload” a rampant and widespread problem. Complex subjects, histories, or issues break …

Identifying and extracting user communities is an important step towards understanding
social network dynamics from a macro perspective. For this reason, the work in this paper …

We propose a neural embedding approach to identify temporally like-minded user
communities, ie, those communities of users who have similar temporal alignment in their …

This paper tackles the problem of detecting temporal content-based user communities from
Twitter. Most existing content-based community detection methods consider the users who …

Stack overflow is a web-based service where users can seek information by asking
questions and share knowledge by providing answers about software development. Ideally …

User communities in social networks are usually identified by considering explicit structural
social connections between users. While such communities can reveal important information …

Medical interventions critically determine clinical outcomes. But prediction models either
ignore interventions or dilute impact by building a single prediction rule by amalgamating …

We propose a temporal latent space model for user community prediction in social networks,
whose goal is to predict future emerging user communities based on past history of users' …

Users in question-answer sites generate huge amounts of high quality and highly reusable
information. This information can be categorized by topics but since users' interests change …