Naslov
Back up your Stance: Recognizing Arguments in Online Discussions

Autori
Boltužić, Filip ; Šnajder, Jan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the First Workshop on Argumentation Mining (ArgMining 2014), Association for Computational Linguistics / - Baltimore (MD) : Association for Computational Linguistics (ACL), 2014, 49-58

Skup
The First Workshop on Argumentation Mining (ArgMining 2014)

Mjesto i datum
Baltimore (MD), Sjedinjene Američke Države, 26.06.2014

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Argumentation mining ; argument recognition ; online discussions ; support vector machines

Sažetak
In online discussions, users often back up their stance with arguments. Their arguments are often vague, implicit, and poorly worded, yet they provide valuable insights into reasons underpinning users’ opinions. In this paper, we make a first step towards argument-based opinion mining from on-line discussions and introduce a new task of argument recognition. We match user- created comments to a set of predefined topic- based arguments, which can be either attacked or supported in the comment. We present a manually- annotated corpus for argument recognition in online discussions. We describe a supervised model based on comment-argument similarity and entailment features. Depending on problem formulation, model performance ranges from 70.5% to 81.8% F1-score, and decreases only marginally when applied to an unseen topic.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA