Topic models have been applied to everything from books to newspapers to social media
posts in an effort to identify the most prevalent themes of a text corpus. We provide an in …

Topic modeling is a popular analytical tool for evaluating data. Numerous methods of topic
modeling have been developed which consider many kinds of relationships and restrictions …

We are not able to deal with a mammoth text corpus without summarizing them into a
relatively small subset. A computational tool is extremely needed to understand such a …

Analyzing short texts infers discriminative and coherent latent topics that is a critical and
fundamental task since many real-world applications require semantic understanding of …

This work creates and makes publicly available the most comprehensive dataset to date
regarding climate change and human opinions via Twitter. It has the heftiest temporal …

Being a prevalent form of social communications on the Internet, billions of short texts are
generated everyday. Discovering knowledge from them has gained a lot of interest from both …

As it covers a wide spectrum, the research literature of human-computer interaction (HCI)
studies has a rich and multi-disciplinary content where there are limited studies …

Social media platforms such as (Twitter, Facebook, and Weibo) are being increasingly
embraced by individuals, groups, and organizations as a valuable source of information …

Many applications require semantic understanding of short texts, and inferring discriminative
and coherent latent topics is a critical and fundamental task in these applications …

Topic models have been prevailing for many years on discovering latent semantics while
modeling long documents. However, for short texts they generally suffer from data sparsity …