Data quality is crucial for training accurate, unbiased, and trustworthy machine learning
models as well as for their correct evaluation. Recent works, however, have shown that even …

Anticipating audience reaction towards a certain piece of text is integral to several facets of
society ranging from politics, research, and commercial industries. Sentiment analysis (SA) …

We propose TuringAdvice, a new challenge task and dataset for language understanding
models. Given a written situation that a real person is currently facing, a model must …

The task of extracting and classifying entities is at the core of important Health-NLP systems
such as misinformation detection, medical dialogue modeling, and patient-centric …

Plain texts written in natural language may have several specific features, such as
organizational patterns and an ambiguous and evolving vocabulary. From the literature …

Anticipating audience reaction towards a certain text is integral to several facets of society
ranging from politics, research, and commercial industries. Sentiment analysis (SA) is a …

This study explores the application of Large Language Models (LLMs) for Emotion Analysis
on social media, focusing on predicting 80 diverse emotions. After comprehensive …

As humans, our understanding of language is grounded in a rich mental model about" how
the world works." As children, we learn this mental model gradually. We take in raw …

There is limited understanding of the user-level variables related to the common activity of
repeat advice-seeking on virtual communities. Gender is of particular interest; past studies …

This paper demonstrates that aggregating crowdsourced forecasts benefits from modeling
the written justifications provided by forecasters. Our experiments show that the majority and …