期刊名称：International Journal of Advanced Computer Research
印刷版ISSN：2249-7277
电子版ISSN：2277-7970
出版年度：2018
卷号：8
期号：39
页码：354-363
出版社：Association of Computer Communication Education for National Triumph (ACCENT)
摘要：Sarcasm detection is an important task in natural language processing (NLP). Sarcasm flips the polarity of a sentence and will affect the accuracy of sentiment analysis task. Recent researches incorporate machine learning and deep learning methods to detect sarcasm. Sarcasm can be detected by the occurrence of context disparity. This feature can be detected by observing the similarity score of each word in the sentence. Word embedding vector is used to calculate word similarity score. In this work, the word similarity score is incorporated as an augmented feature in the deep learning model. Three augmenting schemes in deep learning models are observed. Results show that in general, a word similarity score boosts the performance of the classifier. The accuracy of 85.625% with F-Measure of 84.884% was achieved at its best.
关键词：Sarcasm detection; Word incongruity; Deep learning; Augmented feature.
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