Argumentation Mining: State of the Art and Emerging Trends

@article{Lippi2016ArgumentationMS,
  title={Argumentation Mining: State of the Art and Emerging Trends},
  author={Marco Lippi and Paolo Torroni},
  journal={ACM Trans. Internet Techn.},
  year={2016},
  volume={16},
  pages={10:1-10:25}
}
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… Expand
MARGOT: A web server for argumentation mining
TLDR
The technology behind MARGOT, the first online argumentation mining system designed to reach out to the wider community of potential users of these new technologies, is described and its possible application in the analysis of content from various domains is discussed. Expand
The evolution of argumentation mining: From models to social media and emerging tools
TLDR
This survey article bridges the gap between theoretical approaches of argumentation mining and pragmatic schemes that satisfy the needs of social media generated data, recognizing the need for adapting more flexible and expandable schemes, capable to adjust to the argumentation conditions that exist in social media. Expand
Combining argumentation and aspect-based opinion mining: The SMACk system
TLDR
SMACk, the authors' opinion summary system built on top of an argumentation framework with the aim to exchange, communicate and resolve possibly conflicting viewpoints, allows the user to extract debated opinions from a set of documents containing user-generated content from online commercial websites. Expand
Five Years of Argument Mining: a Data-driven Analysis
TLDR
This paper presents the argument mining tasks, and the obtained results in the area from a data-driven perspective, and highlights the main weaknesses suffered by the existing work in the literature, and proposes open challenges to be faced in the future. Expand
Automatic argumentation mining and the role of stance and sentiment
TLDR
Argumentation mining is a subfield of Computational Linguistics that aims at automatically finding arguments and their structural components in natural language text and two other applications that are popular in computational linguistics: sentiment analysis and stance detection are described. Expand
Argumentation Mining in User-Generated Web Discourse
TLDR
The findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task and offers the data, source codes, and annotation guidelines to the community under free licenses. Expand
Cross-Lingual Argumentation Mining
Argumentation mining is an important task given the multitude of textual sources and contexts it can be applied to. Many previous studies aimed at the analysis of legal documents, or posts in webExpand
Mining Bipolar Argumentation Frameworks from Natural Language Text
TLDR
A methodology for mining topic-dependent Bipolar Argumentation Frameworks (BAFs) from natural language text by identifying attack and support argumentative relations between texts about the same topic is described. Expand
Social Media Argumentation Mining: The Quest for Deliberateness in Raucousness
TLDR
The motivation for social media argumentation mining, as well as the tasks and challenges involved, are discussed. Expand
Argument Mining: A Survey
TLDR
The techniques that establish the foundations for argument mining are explored, a review of recent advances in argument mining techniques are provided, and the challenges faced in automatically extracting a deeper understanding of reasoning expressed in language in general are discussed. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 114 REFERENCES
Argumentation mining
TLDR
This work presents different methods to aid argumentation mining, starting with plain argumentation detection and moving forward to a more structural analysis of the detected argumentation. Expand
Context-Independent Claim Detection for Argument Mining
TLDR
This work proposes a method that exploits structured parsing information to detect claims without resorting to contextual information, and yet achieve a performance comparable to that of state-of-the-art methods that heavily rely on the context. Expand
Mining Economic Sentiment Using Argumentation Structures
TLDR
A framework is proposed that allows the incorporation of information on argumentation structure in the models for economic sentiment discovery in text based on their statistical properties and possibly combined with numeric data. Expand
NoDE: A Benchmark of Natural Language Arguments
TLDR
NoDE is presented, a benchmark of natural language arguments composed of three datasets, built from different textual sources and annotated highlighting positive and negative connections between arguments. Expand
Applying Kernel Methods to Argumentation Mining
TLDR
It is shown that a classification accuracy of 65%, can be attained using Natural Language Processing based kernel approaches, which do not require any heuristic choice of features. Expand
Argumentation Mining on the Web from Information Seeking Perspective
TLDR
It is argued that an annotation scheme for argumentation mining is a function of the task requirements and the corpus properties and it is found that the choice of the argument components to be annotated strongly depends on the register, the length of the document, and inherently on the literary devices and structures used for expressing argumentation. Expand
Integrating argumentation and sentiment analysis for mining opinions from Twitter
TLDR
This paper presents a novel framework which allows to mine opinions from Twitter based on incrementally generated queries, and will be able to obtain an "opinion tree", rooted in the first original query. Expand
Towards segment-based recognition of argumentation structure in short texts
TLDR
A small corpus of German microtexts is collected in a text generation experiment, resulting in texts that are authentic but of controlled linguistic and rhetoric complexity, and it is shown that trained annotators can determine the argumentation structure on thesemicrotexts reliably. Expand
A natural language bipolar argumentation approach to support users in online debate interactions†
TLDR
This paper proposes and evaluates the use of NL techniques to identify the arguments and their relations, and adopts the textual entailment (TE) approach, a generic framework for applied semantical analysis. Expand
From Argument Diagrams to Argumentation Mining in Texts: A Survey
TLDR
The authors provide a critical survey of the literature on both the resulting representations i.e., argument diagramming techniques and on the various aspects of the automatic analysis process. Expand
...
1
2
3
4
5
...