@inproceedings{L16-1200,
 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.
},
 address = {Portorož, Slovenia},
 author = {Tom Bosc and Elena Cabrio and Serena Villata},
 booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
 month = {May},
 pages = {1258--1263},
 publisher = {European Language Resources Association (ELRA)},
 title = {DART: a Dataset of Arguments and their Relations on Twitter},
 url = {https://www.aclweb.org/anthology/L16-1200},
 year = {2016}
}