自然语言处理中反讽检测技术综述

Bhuvanesh Singh, D. Sharma
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引用次数: 0

摘要

讽刺是一种经常在日常对话中使用的语言风格,自然语言处理(NLP)系统可能很难识别。近年来,讽刺在社交媒体、在线评论和其他数字通信中的使用有所增加,这使得NLP系统准确检测讽刺变得至关重要。在本调查中,我们概述了使用NLP技术进行讽刺检测的现状。我们讨论了检测讽刺的各种方法,包括机器学习、深度学习和基于词典的方法。我们还回顾了最近在各种语言和背景下的讽刺检测研究,例如社交媒体,客户评论和在线论坛。我们还确定了未来研究的机会,并解决了当前讽刺检测技术的困难和局限性。本调查的总体目标是通过提供对NLP中讽刺检测的全面掌握来进一步研究这一领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey of Sarcasm Detection Techniques in Natural Language Processing
Sarcasm is a linguistic style that is often employed in regular conversation and that natural language processing (NLP) systems may find difficult to recognize. The use of sarcasm in social media, online reviews, and other digital communication has increased in recent years, making it essential for NLP systems to detect sarcasm accurately. In this survey, we provide an overview of the current state of the art in sarcasm detection using NLP techniques. We discuss the various approaches to detect sarcasm, including machine learning, deep learning, and lexicon-based methods. We also review recent research on sarcasm detection in various languages and contexts, such as social media, customer reviews, and online forums. We also identify opportunities for future study and address the difficulties and limits of the present sarcasm detection techniques. The overall goal of this survey is to further this field of study by providing a thorough grasp of sarcasm detection in NLP.
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