Automatic sarcasm detection using feature selection

P. Dharwal, T. Choudhury, R. Mittal, Praveen Kumar
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引用次数: 20

Abstract

Sarcasm is an expression of humor, mockery or criticism with the help of ironic remarks that seems positive. Sarcasm detection in sentiment analysis is essential for understanding the emotions and thoughts of the people. Automatic sarcasm detection refers to the detection of sarcasm in the text written in natural language. Various natural language processing techniques carry out this purpose. Recognition of Sarcasm is of extraordinary significance and is valuable to numerous NLP applications such as Opinion Mining and multiple advertisings. Sarcasm detection is a complex task, because of the challenges involved in determining the nature of the sarcasm bearing text. Automatic sarcasm detection is thus, one of the hardest challenges in Sentiment Analysis, including complex linguistic analyzing and machine learning methods. This paper focuses on various sarcasm analyzing techniques employed for filtering of sarcastic statements from a text and the use of Automatic sarcasm detection in the categorization of tweets and product review texts.
使用特征选择的自动讽刺检测
讽刺是一种幽默、嘲弄或批评的表达,借助看似积极的讽刺言论。情感分析中的讽刺检测对于理解人的情感和思想是必不可少的。自动讽刺检测是指对自然语言文本中的讽刺进行检测。各种自然语言处理技术实现了这一目的。讽刺的识别具有非凡的意义,对许多NLP应用,如意见挖掘和多种广告都有价值。讽刺检测是一项复杂的任务,因为确定带有讽刺意味的文本的性质是一项挑战。因此,自动讽刺检测是情感分析中最困难的挑战之一,包括复杂的语言分析和机器学习方法。本文重点研究了用于从文本中过滤讽刺语句的各种讽刺分析技术,以及在tweet和产品评论文本分类中使用自动讽刺检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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