用语义标签分析阿拉伯语隐喻的情感，首次实现自动分类
Arabic Metaphor Sentiment Classification Using Semantic Information
- 基于语义情感标签设计新工具，实现阿拉伯语隐喻情感分类
- 在AMC数据集上取得0.78的F-score，验证方法有效性
- 适合研究阿拉伯语文化表达、社交媒体情感分析者
本文探讨使用新设计的自动化工具对阿拉伯语隐喻语料库（AMC）进行情感分类，该工具结合语义情感标签实现分类。通过标准评估指标F-score、召回率和精确率验证工具性能。实验表明，该方法能有效揭示阿拉伯语网络隐喻对情感的影响。据我们所知，这是首个利用语义标签对阿拉伯语隐喻进行情感分类的研究。
原文摘要 · Abstract (English)
In this paper, I discuss the testing of the Arabic Metaphor Corpus (AMC) [1] using newly designed automatic tools for sentiment classification for AMC based on semantic tags. The tool incorporates semantic emotional tags for sentiment classification. I evaluate the tool using standard methods, which are F-score, recall, and precision. The method is to show the impact of Arabic online metaphors on sentiment through the newly designed tools. To the best of our knowledge, this is the first approach to conduct sentiment classification for Arabic metaphors using semantic tags to find the impact of the metaphor.
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