Topic modeling is used in information retrieval to infer the hidden themes in a collection of
documents and thus provides an automatic means to organize, understand and summarize …

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 …

With the growth of online social network platforms and applications, large amounts of textual
user-generated content are created daily in the form of comments, reviews, and short-text …

Topic modeling is one of the most powerful techniques in text mining for data mining, latent
data discovery, and finding relationships among data and text documents. Researchers …

The COVID-19 pandemic influenced people's everyday lives because of the health
emergency and the resulting socio-economic crisis. People use social media to share …

Aspect extraction is an important and challenging task in aspect-based sentiment analysis.
Existing works tend to apply variants of topic models on this task. While fairly successful …

With the widespread use of social networks, blogs, forums and e-commerce web sites, the
volume of user generated textual data is growing exponentially. User opinions in product …

Social media websites can be used as a data source for mining public opinion on a variety
of subjects including climate change. Twitter, in particular, allows for the evaluation of public …

For many applications that require semantic understanding of short texts, inferring
discriminative and coherent latent topics from short texts is a critical and fundamental task …