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Towards Automatic Argument Extraction and Visualization in a Deliberative Model of Online Consultations for Local Governments

机译:面向地方政府的在线咨询协商模型中的自动参数提取和可视化

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Automatic extraction and visualization of arguments used in a long online discussion, especially if the discussion involves a large number of participants and spreads over several days, can be helpful to the people involved. The main benefit is that they do not have to read all entries to get to know the main topics being discussed and can refer to existing arguments instead of introducing them anew. Such discussions take place, i.e., on a deliberative platform being developed under the 'In Dialogue' project. In this paper we propose a framework allowing for automatic extraction of arguments from deliberations and visualization. The framework assumes extraction of arguments and argument proposals, sentiment analysis to predict whether argument is negative or positive, classification to decide how the arguments are related and the use of ontology for visualization.
机译:长时间在线讨论中使用的论据的自动提取和可视化,特别是如果讨论涉及大量参与者并且分散了几天的时间,可能会对相关人员有所帮助。主要优点在于,他们不必阅读所有条目即可了解正在讨论的主要主题,并且可以引用现有参数,而不必重新引入它们。此类讨论是在“对话”项目下开发的协商平台上进行的。在本文中,我们提出了一个框架,允许从讨论和可视化中自动提取参数。该框架假定提取论点和论点建议,进行情感分析以预测论点是消极还是积极,进行分类以决定论点如何关联以及使用本体进行可视化。

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