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首页> 外文会议>International Conference on Social, Cultural, and Behavioral Modeling Prediction and Behavior Representation in Modeling and Simulation >Detecting Agreement and Disagreement in Political Debates
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Detecting Agreement and Disagreement in Political Debates

机译：检测协议和政治辩论中的分歧

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摘要

In this paper, the task of agreement/disagreement detection in political debates is studied. The main goal of this study is to detect agreement/disagreement between two individuals on a topic based on their conversations. This is a challenging task due to the lack of annotated corpora in this field. A self-labeling method is introduced for data collection and generating the training data. A new approach based on text classification is proposed for this task. The experimental results on Canadian Parliamentary debates and the United State 1960 Presidential Campaign datasets have proven the efficiency of the developed methodology and outperforms the baseline methodologies. In addition, the validity of the proposed self-labeling method is evaluated, and its efficiency is confirmed.
机译：本文研究了政治辩论中协议/分歧检测的任务。本研究的主要目标是根据其对话检测两个主题的两个人之间的协议/分歧。由于缺乏该领域的注释语料，这是一个具有挑战性的任务。引入了自我标记方法，用于数据收集并生成培训数据。为此任务提出了一种基于文本分类的新方法。加拿大议会辩论和联合国1960年总统竞选数据集的实验结果证明了开发方法的效率，优于基线方法。此外，评估所提出的自标记方法的有效性，确认其效率。

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