Online social network such as Twitter, Facebook and Instagram are increasingly becoming
the go-to medium for users to acquire information and discuss what is happening globally …

In recent years, studies related to topic derivation in Twitter have gained a lot of interest from
businesses and academics. The interconnection between users and information has made …

Firms collect an enormous amount of user generated content (UGC), such as social media
posts, to analyze consumers' unfiltered opinions regarding brands and firms. A challenge in …

Two developments in computational text analysis widen opportunities for qualitative data
analysis: amounts of digital text worth investigating are growing rapidly, and progress in …

Word meaning changes over time, depending on linguistic and extra-linguistic factors.
Associating a word's correct meaning in its historical context is a central challenge in …

Building alteration and redevelopment play a central role in the revitalization of developed
cities, where the scarcity of available land limits the construction of new buildings. The …

This article presents an unsupervised multi-view hierarchical embedding (UMHE) framework
to sufficiently reveal the intrinsic topical knowledge in social events. Event-oriented topics …

Topic evolution mining on short texts is an important research topic in natural language
processing. Existing methods have been focused either on the topic evolution of normal …

A new framework for improving event detection is proposed that employs joint information in
news media content and social networks, such as Twitter, to leverage detailed coverage of …

We present the Wright-Fisher Indian buffet process (WF-IBP), a probabilistic model for time-
dependent data assumed to have been generated by an unknown number of latent features …