The increasing popularity and diversity of social media sites has encouraged more and
more people to participate on multiple online social networks to enjoy their services. Each …

We develop an online variational Bayes (VB) algorithm for Latent Dirichlet Allocation (LDA).
Online LDA is based on online stochastic optimization with a natural gradient step, which we …

This paper presents an LDA-style topic model that captures not only the low-dimensional
structure of data, but also how the structure changes over time. Unlike other recent work that …

Latent Dirichlet allocation (LDA) and other related topic models are increasingly popular
tools for summarization and manifold discovery in discrete data. However, LDA does not …

This paper presents Online Topic Model (OLDA), a topic model that automatically captures
the thematic patterns and identifies emerging topics of text streams and their changes over …

Topic models provide a powerful tool for analyzing large text collections by representing
high dimensional data in a low dimensional subspace. Fitting a topic model given a set of …

Inference algorithms for topic models are typically designed to be run over an entire
collection of documents after they have been observed. However, in many applications of …

We propose that the information access behavior of a group of people can be modeled as
an information flow issue, in which people intentionally or unintentionally influence and …

Social media anomaly detection is of critical importance to prevent malicious activities such
as bullying, terrorist attack planning, and fraud information dissemination. With the recent …

Employees depend on other people in the enterprise for rapid access to important
information. But current systems for finding experts do not adequately address the social …