Stance Classification of Context-Dependent Claims
Recent work has addressed the problem of detecting relevant claims for a given controversial topic. We introduce the complementary task of Claim Stance Classification, along with the first benchmark dataset for this task. We decompose this problem into: (a) open-domain target identification for topic and claim (b) sentiment classification for each target, and (c) open-domain contrast detection between the topic and the claim targets. Manual annotation of the dataset confirms the applicability and validity of our model. We describe an implementation of our model, focusing on a novel algorithm for contrast detection. Our approach achieves promising results, and is shown to outperform several baselines, which represent the common practice of applying a single, monolithic classifier for stance classification.
Code (0)
등록된 구현이 없습니다.
Tasks
ClassificationGeneral ClassificationSentiment AnalysisSentiment ClassificationStance ClassificationSimilar Papers 제목 키워드 기반
Prompt, Condition, and Generate: Classification of Unsupported Claims with In-Context Learning
Unsupported and unfalsifiable claims we encounter in our daily lives can influence our view of the world. Characterizing, summarizing, and -- more generally -- making sense of such claims, however, can be challenging. In…
Fact CheckingIn-Context LearningSyntopical Graphs for Computational Argumentation Tasks
Approaches to computational argumentation tasks such as stance detection and aspect detection have largely focused on the text of independent claims, losing out on potentially valuable context provided by the rest of the…
Stance DetectionClaims on demand -- an initial demonstration of a system for automatic detection and polarity identification of context dependent claims in massive corpora
STANCY: Stance Classification Based on Consistency Cues
Controversial claims are abundant in online media and discussion forums. A better understanding of such claims requires analyzing them from different perspectives. Stance classification is a necessary step for inferring …
ClassificationGeneral ClassificationStance ClassificationToward Stance Classification Based on Claim Microstructures
Claims are the building blocks of arguments and the reasons underpinning opinions, thus analyzing claims is important for both argumentation mining and opinion mining. We propose a framework for representing claims as mi…
Argument MiningClassificationFine-Grained Opinion AnalysisGeneral Classification+2