有毒评论收集:使30多个数据集在一个统一的格式中易于访问

Julian Risch, Philipp Schmidt, Ralf Krestel
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引用次数: 2

摘要

随着有毒评论分类研究的兴起,越来越多的注释数据集被发布。各种各样的任务(不同的语言,不同的标记过程和方案)导致了大量的异构数据集,可用于训练和测试非常具体的设置。尽管最近努力创建提供概述的网页,但大多数出版物仍然只使用单个数据集。它们不是存储在一个中央数据库中,它们以许多不同的数据格式出现,很难解释它们的类标签以及如何在其他项目中重用这些标签。为了克服这些问题,我们以软件工具的形式提供了三十多个数据集的集合,该软件工具可以自动下载和处理数据,并以统一的数据格式呈现它们,该格式还提供了兼容类标签的映射。该工具的另一个优点是,它提供了可用数据集属性的概述,例如不同的语言、平台和类标签,从而更容易选择合适的训练和测试数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toxic Comment Collection: Making More Than 30 Datasets Easily Accessible in One Unified Format
With the rise of research on toxic comment classification, more and more annotated datasets have been released. The wide variety of the task (different languages, different labeling processes and schemes) has led to a large amount of heterogeneous datasets that can be used for training and testing very specific settings. Despite recent efforts to create web pages that provide an overview, most publications still use only a single dataset. They are not stored in one central database, they come in many different data formats and it is difficult to interpret their class labels and how to reuse these labels in other projects. To overcome these issues, we present a collection of more than thirty datasets in the form of a software tool that automatizes downloading and processing of the data and presents them in a unified data format that also offers a mapping of compatible class labels. Another advantage of that tool is that it gives an overview of properties of available datasets, such as different languages, platforms, and class labels to make it easier to select suitable training and test data.
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