.png){kind=icon}
返回
Automatic Sarcasm Detection: A Survey
.png){kind=icon}
OA
AI
DOI：10.1145/3124420.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text. Beginning with an approach that used speech-based features, automatic sarcasm detection has witnessed great interest from the sentiment analysis community. This article is a compilation of past work in automatic sarcasm detection. We observe three milestones in the research so far: semi-supervised pattern extraction to identify implicit sentiment, use of hashtag-based supervision, and incorporation of context beyond target text. In this article, we describe datasets, approaches, trends, and issues in sarcasm detection. We also discuss representative performance values, describe shared tasks, and provide pointers to future work, as given in prior works. In terms of resources to understand the state-of-the-art, the survey presents several useful illustrations-most prominently, a table that summarizes past papers along different dimensions such as the types of features, annotation techniques, and datasets used.
Keyword:
Sarcasm
sentiment
opinion
sarcasm detection
sentiment analysis
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
28
论文数:
2.4K
被引数:
3.5W
机构
引用论文
One and two sided tests of significance Statsitical hypothesis should be brought into line with clinial hypothesis.png)
BMJ
OAAI
BMJIF0
OAAI分享收藏分享收藏
查看更多内容