Results 11 to 20 of about 4,967,798 (324)
Unsupervised User Stance Detection on Twitter
Proceedings of the International AAAI Conference on Web and Social Media, 2020 We present a highly effective unsupervised framework for detecting the stance of prolific Twitter users with respect to controversial topics. In particular, we use dimensionality reduction to project users onto a low-dimensional space, followed by ...
Aupetit, Michaël +3 more
core +3 more sources
Zero-shot stance detection based on multi-expert collaboration [PDF]
Scientific ReportsZero-shot stance detection is pivotal for autonomously discerning user stances on novel emerging topics. This task hinges on effective feature alignment transfer from known to unseen targets.
Xuechen Zhao +5 more
doaj +2 more sources
A systematic review of machine learning techniques for stance detection and its applications [PDF]
Neural Computing and Applications, 2023 Hamzah Luqman, Moataz Ahmed
exaly +2 more sources
Promises and pitfalls of using LLMs to identify actor stances in political discourse. [PDF]
PLoS ONEEmpirical research in the social sciences is often interested in understanding actor stances; the positions that social actors take regarding normative statements in societal discourse.
Viviane Walker, Mario Angst
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Stance Detection with Explanations
Computational LinguisticsAbstract Identification of stance has recently gained a lot of attention with the extreme growth of fake news and filter bubbles. Over the last decade, many feature-based and deep-learning approaches have been proposed to solve stance detection.
Rudra Ranajee Saha +2 more
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Stance Detection Benchmark: How Robust is Your Stance Detection? [PDF]
KI - Künstliche Intelligenz, 2021 AbstractStance detection (StD) aims to detect an author’s stance towards a certain topic and has become a key component in applications like fake news detection, claim validation, or argument search. However, while stance is easily detected by humans, machine learning (ML) models are clearly falling short of this task.
Benjamin Schiller +2 more
openaire +3 more sources
ACM Computing Surveys, 2020 Automatic elicitation of semantic information from natural language texts is an important research problem with many practical application areas. Especially after the recent proliferation of online content through channels such as social media sites, news portals, and forums; solutions to problems such as sentiment analysis, sarcasm ...
Dilek Küçük, Fazli Can
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A Tutorial on Stance Detection
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022 Date of Conference: February 21 - 25 ...
Kucuk, Dilek, Can, Fazli
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Proceedings of the 2018 Conference of the North American Chapter of
the Association for Computational Linguistics: Demonstrations, 2018 The proliferation of fake news and filter bubbles makes it increasingly difficult to form an unbiased, balanced opinion towards a topic. To ameliorate this, we propose 360° Stance Detection, a tool that aggregates news with multiple perspectives on a topic.
Sebastian Ruder +3 more
openaire +2 more sources
X-Stance: A Multilingual Multi-Target Dataset for Stance Detection [PDF]
CoRR, 2020 SwissText + KONVENS 2020.
Vamvas, Jannis, Sennrich, Rico
openaire +4 more sources