From Argument Diagrams to Argumentation Mining in Texts: A Survey

نویسندگان

  • Andreas Peldszus
  • Manfred Stede
چکیده

In this paper, the authors consider argument mining as the task of building a formal representation for an argumentative piece of text. Their goal is to 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. For representation, the authors also provide a synthesized proposal of a scheme that combines advantages from several of the earlier approaches; in addition, the authors discuss the relationship between representing argument structure and the rhetorical structure of texts in the sense of Mann and Thompsons (1988) RST. Then, for the argument mining problem, the authors also cover the literature on closely-related tasks that have been tackled in Computational Linguistics, because they think that these can contribute to more powerful argument mining systems than the first prototypes that were built in recent years. The paper concludes with the authors’ suggestions for the major challenges that should be addressed in the field of argument mining. From Argument Diagrams to Argumentation Mining in Texts: A Survey

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Using Argument Mining to Assess the Argumentation Quality of Essays

Argument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of p...

متن کامل

Latest News in Computational Argumentation: Surfing on the Deep Learning Wave, Scuba Diving in the Abyss of Fundamental Questions

Mining arguments from natural language texts, parsing argumentative structures, and assessing argument quality are among the recent challenges tackled in computational argumentation. While advanced deep learning models provide state-of-theart performance in many of these tasks, much attention is also paid to the underlying fundamental questions. How are arguments expressed in natural language a...

متن کامل

Joint prediction in MST-style discourse parsing for argumentation mining

We introduce a new approach to argumentation mining that we applied to a parallel German/English corpus of short texts annotated with argumentation structure. We focus on structure prediction, which we break into a number of subtasks: relation identification, central claim identification, role classification, and function classification. Our new model jointly predicts different aspects of the s...

متن کامل

A News Editorial Corpus for Mining Argumentation Strategies

Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude. This includes decisions such as when to tell an anecdote or where to support an assumption with statistics, which is reflected by the composition of different types of argumentative discourse units in a text. While several argument mining corpora have re...

متن کامل

A classification system for argumentation schemes

This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • IJCINI

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2013