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首页> 外文会议>Conference on the North American Chapter of the Association for Computational Linguistics: Human Language Technologies >From Legal to Technical Concept: Towards an Automated Classification of German Political Twitter Postings as Criminal Offenses
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From Legal to Technical Concept: Towards an Automated Classification of German Political Twitter Postings as Criminal Offenses

机译：从合法到技术概念：朝着德国政治推特邮寄的自动分类为刑事罪行

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Advances in the automated detection of offensive Internet postings make this mechanism very attractive to social media companies, who are increasingly under pressure to monitor and action activity on their sites. However, these advances also have important implications as a threat to the fundamental right of free expression. In this article, we analyze which Twitter posts could actually be deemed offenses under German criminal law. German law follows the deductive method of the Roman law tradition based on abstract rules as opposed to the inductive reasoning in Anglo-American common law systems. This allows us to show how legal conclusions can be reached and implemented without relying on existing court decisions. We present a data annotation schema, consisting of a series of binary decisions, for determining whether a specific post would constitute a criminal offense. This schema serves as a step towards an inexpensive creation of a sufficient amount of data for automated classification. We find that the majority of posts deemed morally offensive actually do not constitute a criminal offense and still contribute to public discourse. Furthermore, laymen can provide sufficiently reliable data to an expert reference but are, for instance, more lenient in the interpretation of what constitutes a disparaging statement.
机译：进攻互联网邮政的自动检测的进步使得这种机制对社交媒体公司非常有吸引力，他越来越受到在其网站上监控和行动活动的压力。但是，这些进步也对对自由表达的基本权利的威胁具有重要意义。在本文中，我们分析了哪些推特员额实际上可以在德国刑法下被视为罪行。德国法律遵循罗马法传统的演绎方法，基于抽象规则而不是盎格鲁 - 美国普通法制度的归纳推理。这使我们能够展示如何在不依赖现行法院的决定的情况下达成和实施法律结论。我们介绍了一个由一系列二元决策组成的数据注释模式，以确定特定职位是否构成刑事犯罪。该模式用于朝着廉价创建用于自动分类量的廉价创建的一步。我们发现，大多数帖子被视为道德冒犯的实际上不构成刑事犯罪，仍然有助于公众话语。此外，Laymen可以向专家参考提供足够可靠的数据，但是例如，在解释构成差异声明的情况下，更宽度。

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