Stance detection on social media is an emerging opinion mining paradigm for various social
and political applications in which sentiment analysis may be sub-optimal. There has been a …

Stance detection is an evolving opinion mining research area motivated by the vast increase
in the variety and volume of user-generated content. In this regard, considerable research …

Large language models (LLMs) are capable of successfully performing many language
processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify …

The prevalence of the COVID-19 pandemic in day-to-day life has yielded large amounts of
stance detection data on social media sites, as users turn to social media to share their …

Stance detection on social media can help to identify and understand slanted news or
commentary in everyday life. In this work, we propose a new model for zero-shot stance …

Hate Speech and harassment are widespread in online communication, due to users'
freedom and anonymity and the lack of regulation provided by social media platforms. Hate …

Stance detection determines whether the author of a text is in favor of, against or neutral to a
specific target and provides valuable insights into important events such as presidential …

The goal of stance detection is to determine the viewpoint expressed in a piece of text
towards a target. These viewpoints or contexts are often expressed in many different …

Users rely heavily on social media to consume and share news, facilitating the mass dis-
semination of genuine and fake stories. The proliferation of misinformation on various social …

SardiStance is the first shared task for Italian on the automatic classification of stance in
tweets. It is articulated in two different settings: A) Textual Stance Detection, exploiting only …