Stance Detection and Open Research Avenues
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 29 references that are in the map. First posted on arXiv 22 Oct 2022.
Builds on
7 of 29 references.
References · 7
- 2020Stance Detection on Social Media: State of the Art and Trendscited by 95
- 2017Beyond News Contents: The Role of Social Context for Fake News Detectioncited by 91
- 2019A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Fillingcited by 85
- 2020Stance Detection Benchmark: How Robust Is Your Stance Detection?cited by 33
- 2021Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Trainingcited by 28
- 2019Contrastive Language Adaptation for Cross-Lingual Stance Detectioncited by 18
- 2022A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learningcited by 10
Built on by
Not cited yet.