Stance Detection and Open Research Avenues
It provides a comprehensive overview for researchers and practitioners in stance detection and related domains, but is incremental as it synthesizes existing knowledge rather than presenting new findings.
This tutorial addresses the problem of stance detection, a recent research topic for determining stances from content, by covering state-of-the-art methods and open research avenues, aiming to guide researchers and practitioners in fields like social media analysis and NLP.
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.