论文标题
搜索宠物：使用基于分布和情感的方法来查找潜在的委婉术语
Searching for PETs: Using Distributional and Sentiment-Based Methods to Find Potentially Euphemistic Terms
论文作者
论文摘要
本文介绍了以语言驱动的概念证明，以查找潜在的委婉术语或宠物。承认宠物倾向于在一定范围的敏感主题中通常使用表达式，因此我们利用分布相似性从句子中选择和过滤短语候选者，并使用一组简单的基于情感的指标对它们进行排名。我们介绍了我们对包含委婉语的句子的测试的方法的结果，证明了其在广泛主题中检测单词和多词宠物的功效。我们还讨论了基于情感的方法的未来潜力。
This paper presents a linguistically driven proof of concept for finding potentially euphemistic terms, or PETs. Acknowledging that PETs tend to be commonly used expressions for a certain range of sensitive topics, we make use of distributional similarities to select and filter phrase candidates from a sentence and rank them using a set of simple sentiment-based metrics. We present the results of our approach tested on a corpus of sentences containing euphemisms, demonstrating its efficacy for detecting single and multi-word PETs from a broad range of topics. We also discuss future potential for sentiment-based methods on this task.
