An Automated Deep Learning Model for Detecting Sarcastic Comments

Jaico Jose, Preethi N
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Abstract

The concept of Natural Language Processing is immensely vast with a wide range of fields in which ideas can be explored and innovations can be developed. An algorithm based on deep learning is used to detect sarcasm in text in this paper. It is usually only possible to detect sarcasm through speech and very rarely through text. 1.3 million comments from Reddit were analyzed, of which half were sarcastic and half were not, and then various deep learning models were applied, such as standard neural networks, CNNs, and LSTM RNNs. The best performing model was LSTM-RNNs, followed by CNNs, and standard neural networks came last. With textual data, it is much harder to understand whether the other person is being sarcastic or not, it can only be understood by listening to their tone of voice or looking at their behaviour. The purpose of this paper is to demonstrate how to detect sarcasm in textual data using deep learning models.
用于检测讽刺评论的自动深度学习模型
自然语言处理的概念是非常广阔的,有很多领域可以探索和创新。本文提出了一种基于深度学习的文本讽刺检测算法。通常只有通过言语才能发现讽刺,很少通过文本。分析来自Reddit的130万条评论,其中一半是讽刺,一半不是,然后应用各种深度学习模型,如标准神经网络,cnn, LSTM rnn。表现最好的模型是lstm - rnn,其次是cnn,最后是标准神经网络。有了文字数据,就很难理解对方是否在讽刺,只能通过听他们的语气或观察他们的行为来理解。本文的目的是演示如何使用深度学习模型在文本数据中检测讽刺。
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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