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}
}
  • Marco Lippi, Paolo Torroni
  • Published 2016
  • Computer Science
  • ACM Trans. Internet Techn.
  • 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… CONTINUE READING
    246 Citations
    MARGOT: A web server for argumentation mining
    • 43
    • PDF
    Five Years of Argument Mining: a Data-driven Analysis
    • 55
    • Highly Influenced
    • PDF
    Cross-Lingual Argumentation Mining
    • PDF
    Mining Bipolar Argumentation Frameworks from Natural Language Text
    • 2
    • PDF
    Argumentation Mining in User-Generated Web Discourse
    • 130
    • PDF
    Argument Mining: A Survey
    • 40
    • PDF

    References

    SHOWING 1-10 OF 15 REFERENCES
    Argumentation mining
    • 238
    • Highly Influential
    • PDF
    Argumentation Mining on the Web from Information Seeking Perspective
    • 65
    • Highly Influential
    • PDF
    Towards Argument Mining from Dialogue
    • 34
    • Highly Influential
    • PDF
    A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics
    • 91
    • Highly Influential
    • PDF
    Automatic knowledge extraction from documents
    • 117
    • Highly Influential
    • PDF
    Identifying Justifications in Written Dialogs by Classifying Text as Argumentative
    • 51
    • Highly Influential
    • PDF
    Integrating Probabilistic Extraction Models and Data Mining to Discover Relations and Patterns in Text
    • 193
    • Highly Influential
    • PDF
    Context Dependent Claim Detection
    • 141
    • Highly Influential
    • PDF
    Integrating Collaborative Filtering and Sentiment Analysis: A Rating Inference Approach
    • 105
    • Highly Influential
    • PDF
    On the Role of Discourse Markers for Discriminating Claims and Premises in Argumentative Discourse
    • 65
    • Highly Influential
    • PDF