Argumentation mining aims at automatically extracting structured arguments from unstructured textual documents. It has recently become a hot topic also due to its potential in processing information originating from the Web, and in particular from social media, in innovative ways. Recent advances in machine learning methods promise to enable breakthrough applications to social and economic sciences, policy making, and information technology: something that only a few years ago was unthinkable. In this survey article, we introduce argumentation models and methods, review existing systems and applications, and discuss challenges and perspectives of this exciting new research area.
%0 Journal Article
%1 lippi2016argumentation
%A Lippi, Marco
%A Torroni, Paolo
%C New York, NY, USA
%D 2016
%I ACM
%J ACM Trans. Internet Technol.
%K argument mining toread
%N 2
%P 10:1--10:25
%R 10.1145/2850417
%T Argumentation Mining: State of the Art and Emerging Trends
%U http://doi.acm.org/10.1145/2850417
%V 16
%X Argumentation mining aims at automatically extracting structured arguments from unstructured textual documents. It has recently become a hot topic also due to its potential in processing information originating from the Web, and in particular from social media, in innovative ways. Recent advances in machine learning methods promise to enable breakthrough applications to social and economic sciences, policy making, and information technology: something that only a few years ago was unthinkable. In this survey article, we introduce argumentation models and methods, review existing systems and applications, and discuss challenges and perspectives of this exciting new research area.
@article{lippi2016argumentation,
abstract = {Argumentation mining aims at automatically extracting structured arguments from unstructured textual documents. It has recently become a hot topic also due to its potential in processing information originating from the Web, and in particular from social media, in innovative ways. Recent advances in machine learning methods promise to enable breakthrough applications to social and economic sciences, policy making, and information technology: something that only a few years ago was unthinkable. In this survey article, we introduce argumentation models and methods, review existing systems and applications, and discuss challenges and perspectives of this exciting new research area.},
acmid = {2850417},
added-at = {2018-04-16T21:57:18.000+0200},
address = {New York, NY, USA},
articleno = {10},
author = {Lippi, Marco and Torroni, Paolo},
biburl = {https://www.bibsonomy.org/bibtex/22566fa396fcc63b5e6566dc717cecce6/hotho},
description = {Argumentation Mining},
doi = {10.1145/2850417},
interhash = {423ee46d07d10c3c70d378db2bb9a03f},
intrahash = {2566fa396fcc63b5e6566dc717cecce6},
issn = {1533-5399},
issue_date = {April 2016},
journal = {ACM Trans. Internet Technol.},
keywords = {argument mining toread},
month = mar,
number = 2,
numpages = {25},
pages = {10:1--10:25},
publisher = {ACM},
timestamp = {2018-04-16T21:57:18.000+0200},
title = {Argumentation Mining: State of the Art and Emerging Trends},
url = {http://doi.acm.org/10.1145/2850417},
volume = 16,
year = 2016
}