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Detecting Satire in Italian Political Commentaries

机译：在意大利政治评论中发现讽刺

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This paper presents computational work to detect satire/sarcasm in long commentaries on Italian politics. It uses the lexica extracted from the manual annotation based on Appraisal Theory, of some 30 K word texts. The underlying hypothesis is that using this framework it is possible to precisely pinpoint ironic content through the deep semantic analysis of evaluative judgement and appreciation. The paper presents the manual annotation phase realized on 112 texts by two well-known Italian journalists. After a first experimentation phase based on the lexica extracted from the xml output files, we proceeded to retag lexical entries dividing them up into two subclasses: figurative and literal meaning. Finally more fine-grained Appraisal features have been derived and more experiments have been carried out and compared to results obtained by a lean sentiment analysis. The final output is produced from held out texts to verify the usefulness of the lexica and the Appraisal theory in detecting ironic content.
机译：本文介绍了在对意大利政治进行长时间评论时发现讽刺/嘲讽的计算工作。它使用基于评估理论从手动注释中提取的词汇，约30 K个单词文本。潜在的假设是，使用此框架，可以通过对评价判断和欣赏的深入语义分析来精确地找出具有讽刺意味的内容。本文介绍了由两名意大利著名新闻工作者在112种文本上实现的手动注释阶段。在基于从xml输出文件中提取的词汇的第一个实验阶段之后，我们开始重新标记词汇条目，将其分为两个子类：比喻含义和文字含义。最后，获得了更细粒度的评估功能，并进行了更多的实验，并将其与通过精益情感分析获得的结果进行了比较。最终的输出是从坚持下来的文本中得出的，以验证词典和评估理论在检测讽刺内容中的有用性。

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