Natural language processing (NLP), or the pragmatic research perspective of computational
linguistics, has become increasingly powerful due to data availability and various …

Large language models have led to remarkable progress on many NLP tasks, and
researchers are turning to ever-larger text corpora to train them. Some of the largest corpora …

The advent of massive amounts of textual, audio, and visual data has spurred the
development of econometric methodology to transform qualitative sentiment data into …

Sentiment analysis as a field has come a long way since it was first introduced as a task
nearly 20 years ago. It has widespread commercial applications in various domains like …

Background Social media is a rich source where we can learn about people's reactions to
social issues. As COVID-19 has impacted people's lives, it is essential to capture how …

Recent years have witnessed a surge of publications aimed at tracing temporal changes in
lexical semantics using distributional methods, particularly prediction-based word …

Users organize themselves into communities on web platforms. These communities can
interact with one another, often leading to conflicts and toxic interactions. However, little is …

Opinion mining from customer reviews has become pervasive in recent years. Sentences in
reviews, however, are usually classified independently, even though they form part of a …

Mental disorders can severely affect quality of life, constitute a major predictive factor of
suicide, and are usually underdiagnosed and undertreated. Early detection of signs of …

We provide an NLP framework to uncover four linguistic dimensions of political polarization
in social media: topic choice, framing, affect and illocutionary force. We quantify these …