.png){kind=icon}
返回
A Universal Model for Discourse-Level Argumentation Analysis
.png){kind=icon}
PRE
AI
DOI：10.1145/2957757.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The argumentative structure of texts is increasingly exploited for analysis tasks, for example, for stance classification or the assessment of argumentation quality. Most existing approaches, however, model only the local structure of single arguments. This article considers the question of how to capture the global discourse-level structure of a text for argumentation-related analyses. In particular, we propose to model the global structure as a flow of task-related rhetorical moves, such as discourse functions or aspect based sentiment. By comparing the flow of a text to a set of common flow patterns, we map the text into the feature space of global structures, thus capturing its discourse-level argumentation. We show how to identify different types of flow patterns, and we provide evidence that they generalize well across different domains of texts. In our evaluation for two analysis tasks, the classification of review sentiment and the scoring of essay organization, the features derived from flow patterns prove both effective and more robust than strong baselines. We conclude with a discussion of the universality of modeling flow for discourse-level argumentation analysis.
Keyword:
Argumentation
discourse-level structure
sentiment flow
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.1
论文数:
896
被引数:
1.9K
机构
引用论文
.png){kind=icon}
First record of the non-indigenous jellyfish Blackfordia virginica (Mayer, 1910) in the Baltic Sea
OAAI
OAAI分享收藏Bioactive Compost: An Approach for Managing Plant Growth in Environmentally Stressed Soils生物活性堆肥：一种管理环境胁迫土壤中植物生长的方法
PREAI
分享收藏Efficient organic DSSC sensitizers bearing an electron-deficient pyrimidine as an effective π-spacer
PREAI
分享收藏分享收藏
查看更多内容