Challenge: Several studies have focused on the identification and classification of argumentative components and the argumentative relations between the components.
Approach: They propose an annotation scheme and corpus that captures user-generated inner-post arguments and inter-post relations between users in ChangeMyView.
Outcome: The proposed annotation scheme captures user-generated inner-post arguments and inter-post relations in ChangeMyView, a persuasive forum.

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Annotating and Analyzing Semantic Role of Elementary Units and Relations in Online Persuasive Arguments (P19-2)

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Challenge: Existing studies on the features of persuasiveness focus on lexical features and argumentative features.
Approach: They propose an annotation scheme that captures the semantic role of arguments in a popular online persuasion forum, ChangeMyView.
Outcome: The proposed scheme captures the semantic role of arguments in a popular online persuasion forum, so-called ChangeMyView.
A Multi-layer Annotated Corpus of Argumentative Text: From Argument Schemes to Discourse Relations (L18-1)

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Challenge: Recent interest in Argumentation Mining has brought to the fore the need for corpora annotated with argument information, which can be used as training data.
Approach: They propose a set of guidelines for the annotation of argument schemes and a new annotation tool for the 'inferential' argument schemes.
Outcome: The proposed corpus includes 112 argumentative microtexts and a new annotation tool.
Unveiling the Power of Argument Arrangement in Online Persuasive Discussions (2023.findings-emnlp)

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Challenge: a recent study shows that the CMV is the best time period in human history for the vast majority of people.
Approach: They extend a semantic argumentation unit type model by clustering type sequences into different argument arrangement patterns and representing discussions as sequences of these patterns.
Outcome: The proposed model outperforms existing classifiers on the change my view forum discussion data.
A Corpus for Modeling User and Language Effects in Argumentation on Online Debating (P19-1)

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Challenge: Existing argumentation datasets have allowed only limited assessment of "user" traits because information on background of users is generally unavailable.
Approach: They present a dataset of 78,376 debates generated over a 10-year period along with surprisingly comprehensive participant profiles.
Outcome: The proposed dataset includes 78,376 debates generated over a 10-year period along with comprehensive participant profiles.
A Corpus for Argumentative Writing Support in German (2020.coling-main)

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Challenge: In today's world most information is readily available. Consequently, the sole reproduction of information is losing attention.
Approach: They propose an annotation approach to capture claims and premises of arguments and their relations in student-written peer reviews on business models in german language.
Outcome: The proposed annotation scheme guides annotators to moderate agreement with the proposed scheme on 50 persuasive student-written peer reviews on business models.
AMPERSAND: Argument Mining for PERSuAsive oNline Discussions (D19-1)

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Challenge: Argument mining is a field of corpus-based discourse analysis that involves the automatic identification of argumentative structures in text.
Approach: They propose a computational model for argument mining in online persuasive discussion forums that brings together the micro-level (argument as product) and macro-level models of argumentation.
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Give Me More Feedback: Annotating Argument Persuasiveness and Related Attributes in Student Essays (P18-1)

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Challenge: Existing work on automated essay scoring has focused on holistic scoring, which summarizes the quality of an essay with a single score.
Approach: They present a corpus of essays simultaneously annotated with argument components, argument persuasiveness scores, and attributes of argument components that impact an argument’s persuasiveness.
Outcome: The proposed corpus could trigger the development of novel computational models that provide useful feedback to students on why their arguments are (un)persuasive .
The Discussion Tracker Corpus of Collaborative Argumentation (2020.lrec-1)

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Challenge: The Discussion Tracker corpus is an annotated dataset of transcripts of spoken, multi-party argumentation transcribed from 985 minutes of audio .
Approach: They analyze 29 multi-party arguments transcribed from 985 minutes of audio . they provide descriptive statistics and code for predicting each dimension separately.
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Annotating Arguments in a Corpus of Opinion Articles (2022.lrec-1)

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Challenge: Argument annotation is the process of exposing and justifying one's points of view, with the aim of conveying a logical reasoning through a set of semantically related propositions.
Approach: They propose to use argumentative discourse units to annotate arguments in Portuguese using a multi-layered process to analyze the annotations produced.
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Modeling Persuasive Discourse to Adaptively Support Students’ Argumentative Writing (2022.acl-long)

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Challenge: Argumentation is an omnipresent rudiment of daily communication and thinking . humans struggle to develop argumentation skills due to a lack of individual and instant feedback in their learning process.
Approach: They propose an argumentation annotation approach to model argumentative discourse in student-written business model pitches and embed it into an adaptive writing support system for students that provides individual argumentation feedback.
Outcome: The proposed method annotates a corpus of 200 business model pitches in german and measures their self-efficacy and ease-of-use in a real-world writing exercise.

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