Unsupervised Detection of Argumentative Units though Topic Modeling Techniques
In this paper we present a new unsupervised approach, {``}Attraction to Topics{''} {--} A2T , for the detection of argumentative units, a sub-task of argument mining. Motivated by the importance of topic identification in manual annotation, we examine whether topic modeling can be used for performing unsupervised detection of argumentative sentences, and to what extend topic modeling can be used to classify sentences as claims and premises. Preliminary evaluation results suggest that topic information can be successfully used for the detection of argumentative sentences, at least for corpora used for evaluation. Our approach has been evaluated on two English corpora, the first of which contains 90 persuasive essays, while the second is a collection of 340 documents from user generated content.
Code (0)
등록된 구현이 없습니다.
Tasks
Argument MiningOpinion MiningStance DetectionSimilar Papers 제목 키워드 기반
Computational Argumentation Synthesis as a Language Modeling Task
Synthesis approaches in computational argumentation so far are restricted to generating claim-like argument units or short summaries of debates. Ultimately, however, we expect computers to generate whole new arguments fo…
Language ModelingLanguage ModellingUnsupervised corpus--wide claim detection
Automatic claim detection is a fundamental argument mining task that aims to automatically mine claims regarding a topic of consideration. Previous works on mining argumentative content have assumed that a set of relevan…
Argument MiningDecision MakingSentenceDave the debater: a retrieval-based and generative argumentative dialogue agent
In this paper, we explore the problem of developing an argumentative dialogue agent that can be able to discuss with human users on controversial topics. We describe two systems that use retrieval-based and generative mo…
Argument MiningRetrievalStance DetectionUnsupervised stance detection for arguments from consequences
Social media platforms have become an essential venue for online deliberation where users discuss arguments, debate, and form opinions. In this paper, we propose an unsupervised method to detect the stance of argumentati…
Stance DetectionThe GDN-CC Dataset: Automatic Corpus Clarification for AI-enhanced Democratic Citizen Consultations
LLMs are ubiquitous in modern NLP, and while their applicability extends to texts produced for democratic activities such as online deliberations or large-scale citizen consultations, ethical questions have been raised f…