As massive repositories of real-time human commentary, social media platforms have
arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis …

Qualitative studies, such as sociological research, opinion analysis and media studies, can
benefit greatly from automated topic mining provided by topic models such as latent Dirichlet …

Social media provides valuable resources to analyze user behaviors and capture user
preferences. This article focuses on analyzing user behaviors in social media systems and …

Understanding how topics in scientific literature evolve is an interesting and important
problem. Previous work simply models each paper as a bag of words and also considers the …

Social media provides valuable resources to analyze user behaviors and capture user
preferences. This paper focuses on analyzing user behaviors in social media systems and …

Understanding topic evolution in a scientific domain is essential for capturing key domain
developments and facilitating knowledge transfer within and across domains. Using a data …

现实生活中不断有新话题的产生和旧话题的衰减, 同时话题的内容也会随着时间发生变化.
自动探测话题随时间的演化越来越受到人们的关注. Latent Dirichlet Allocation …

Accurately representing the quantity and characteristics of users' interest in certain topics is
an important problem facing topic evolution researchers, particularly as it applies to modern …

Word meanings change over time. Detecting shifts in meaning for particular words has been
the focus of much research recently. We address the complementary problem of monitoring …

Web 2.0 users generate and spread huge amounts of messages in online social media.
Such user-generated contents are mixture of temporal topics (eg, breaking events) and …