Papers Stance Classification
“Stance Classification” 태그가 달린 논문 101편 · 필터 해제
AQE: Argument Quadruplet Extraction via a Quad-Tagging Augmented Generative Approach
Argument mining involves multiple sub-tasks that automatically identify argumentative elements, such as claim detection, evidence extraction, stance classification, etc. However, each subtask alone is insufficient for a …
Argument MiningStance ClassificationvalidTotalDefMeme: A Multi-Attribute Meme dataset on Total Defence in Singapore
Total Defence is a defence policy combining and extending the concept of military defence and civil defence. While several countries have adopted total defence as their defence policy, very few studies have investigated …
AttributeStance ClassificationExamining Temporalities on Stance Detection towards COVID-19 Vaccination
Previous studies have highlighted the importance of vaccination as an effective strategy to control the transmission of the COVID-19 virus. It is crucial for policymakers to have a comprehensive understanding of the publ…
Stance ClassificationStance DetectionCan We Identify Stance Without Target Arguments? A Study for Rumour Stance Classification
Considering a conversation thread, rumour stance classification aims to identify the opinion (e.g. agree or disagree) of replies towards a target (rumour story). Although the target is expected to be an essential compone…
ClassificationSentiment AnalysisStance ClassificationTopic Ontologies for Arguments
Many computational argumentation tasks, like stance classification, are topic-dependent: the effectiveness of approaches to these tasks significantly depends on whether the approaches were trained on arguments from the s…
Stance ClassificationTopic coverageDoubleH: Twitter User Stance Detection via Bipartite Graph Neural Networks
Given the development and abundance of social media, studying the stance of social media users is a challenging and pressing issue. Social media users express their stance by posting tweets and retweeting. Therefore, the…
Graph Neural NetworkStance ClassificationStance DetectionEnolp musk@SMM4H’22 : Leveraging Pre-trained Language Models for Stance And Premise Classification
This paper covers our approaches for the Social Media Mining for Health (SMM4H) Shared Tasks 2a and 2b. Apart from the baseline architectures, we experiment with Parts of Speech (PoS), dependency parsing, and Tf-Idf feat…
ClassificationDependency ParsingPOSStance ClassificationDebating Europe: A Multilingual Multi-Target Stance Classification Dataset of Online Debates
We present a new dataset of online debates in English, annotated with stance. The dataset was scraped from the “Debating Europe” platform, where users exchange opinions over different subjects related to the European Uni…
Stance ClassificationXLM-RDistant finetuning with discourse relations for stance classification
Approaches for the stance classification task, an important task for understanding argumentation in debates and detecting fake news, have been relying on models which deal with individual debate topics. In this paper, in…
ClassificationStance ClassificationA Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learning
The diffusion of rumors on microblogs generally follows a propagation tree structure, that provides valuable clues on how an original message is transmitted and responded by users over time. Recent studies reveal that ru…
Binary ClassificationMultiple Instance LearningStance ClassificationStance DetectionIAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Tasks
Traditionally, a debate usually requires a manual preparation process, including reading plenty of articles, selecting the claims, identifying the stances of the claims, seeking the evidence for the claims, etc. As the A…
Argument MiningArticlesClaim-Evidence Pair Extraction (CEPE)Claim Extraction with Stance Classification (CESC)+1Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification
Classification of posts in social media such as Twitter is difficult due to the noisy and short nature of texts. Sequence classification models based on recurrent neural networks (RNN) are popular for classifying posts t…
ClassificationRumour DetectionStance Classificationtext-classification+1A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Tasks
Traditionally, a debate usually requires a manual preparation process, including reading plenty of articles, selecting the claims, identifying the stances of the claims, seeking the evidences for the claims, etc. As the …
Argument MiningArticlesClaim-Evidence Pair Extraction (CEPE)Claim Extraction with Stance Classification (CESC)+1On Classifying whether Two Texts are on the Same Side of an Argument
To ease the difficulty of argument stance classification, the task of same side stance classification (S3C) has been proposed. In contrast to actual stance classification, which requires a substantial amount of domain kn…
ClassificationStance ClassificationTribrid: Stance Classification with Neural Inconsistency Detection
We study the problem of performing automatic stance classification on social media with neural architectures such as BERT. Although these architectures deliver impressive results, their level is not yet comparable to the…
ClassificationFact CheckingStance ClassificationOpinions are Made to be Changed: Temporally Adaptive Stance Classification
Given the rapidly evolving nature of social media and people's views, word usage changes over time. Consequently, the performance of a classifier trained on old textual data can drop dramatically when tested on newer dat…
ClassificationStance ClassificationWord EmbeddingsAdvances in Debating Technologies: Building AI That Can Debate Humans
The tutorial focuses on Debating Technologies, a sub-field of computational argumentation defined as {``}computational technologies developed directly to enhance, support, and engage with human debating{''} (Gurevych et …
Argument MiningStance ClassificationContent-based Stance Classification of Tweets about the 2020 Italian Constitutional Referendum
On September 2020 a constitutional referendum was held in Italy. In this work we collect a dataset of 1.2M tweets related to this event, with particular interest to the textual content shared, and we design a hashtag-bas…
Stance ClassificationAmbiFC: Fact-Checking Ambiguous Claims with Evidence
Automated fact-checking systems verify claims against evidence to predict their veracity. In real-world scenarios, the retrieved evidence may not unambiguously support or refute the claim and yield conflicting but valid …
Claim VerificationEvidence SelectionFact CheckingSentence+3Revisiting Rumour Stance Classification: Dealing with Imbalanced Data
Correctly classifying stances of replies can be significantly helpful for the automatic detection and classification of online rumours. One major challenge is that there are considerably more non-relevant replies (commen…
ClassificationRumour DetectionStance Classification