Stance Detection and Open Research Avenues

TL;DR

This tutorial provides a comprehensive overview of stance detection, highlighting recent advances, fundamental concepts, and open research challenges, aiming to guide researchers and practitioners in the field.

Contribution

It offers a structured summary of current methods and identifies key open research avenues in stance detection for social media and NLP applications.

Findings

Overview of state-of-the-art stance detection techniques

Identification of open research challenges and future directions

Resource compilation for stance detection research

Abstract

This tutorial aims to cover the state-of-the-art on stance detection and address open research avenues for interested researchers and practitioners. Stance detection is a recent research topic where the stance towards a given target or target set is determined based on the given content and there are significant application opportunities of stance detection in various domains. The tutorial comprises two parts where the first part outlines the fundamental concepts, problems, approaches, and resources of stance detection, while the second part covers open research avenues and application areas of stance detection. The tutorial will be a useful guide for researchers and practitioners of stance detection, social media analysis, information retrieval, and natural language processing.