DART: a Dataset of Arguments and their Relations on Twitter

Tom Bosc 1, * Elena Cabrio 1 Serena Villata 1
* Auteur correspondant
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : The problem of understanding the stream of messages exchanged on social media such as Facebook and Twitter is becoming a major challenge for automated systems. The tremendous amount of data exchanged on these platforms as well as the specific form of language adopted by social media users constitute a new challenging context for existing argument mining techniques. In this paper, we describe a resource of natural language arguments called DART (Dataset of Arguments and their Relations on Twitter) where the complete argument mining pipeline over Twitter messages is considered: (i) we identify which tweets can be considered as arguments and which cannot, and (ii) we identify what is the relation, i.e., support or attack, linking such tweets to each other.
Type de document :
Communication dans un congrès
Proceedings of the 10th edition of the Language Resources and Evaluation Conference, May 2016, Portoroz, Slovenia. pp.1258-1263
Liste complète des métadonnées

https://hal.inria.fr/hal-01332336
Contributeur : Elena Cabrio <>
Soumis le : mercredi 15 juin 2016 - 16:27:12
Dernière modification le : jeudi 23 juin 2016 - 09:26:23

Fichier

611_Paper.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01332336, version 1

Collections

Citation

Tom Bosc, Elena Cabrio, Serena Villata. DART: a Dataset of Arguments and their Relations on Twitter. Proceedings of the 10th edition of the Language Resources and Evaluation Conference, May 2016, Portoroz, Slovenia. pp.1258-1263. <hal-01332336>

Partager

Métriques

Consultations de
la notice

156

Téléchargements du document

89