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A Comparative Analysis of Opinion Mining and Sentiment Classification in Non-english Languages

机译:非英语语言中意见挖掘与情感分类的比较分析

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摘要

In the past decade many opinion mining and sentiment classification studies have been carried out for opinions in English. However, the amount of work done for non-English text opinions is very limited.In this review, we investigate opinion mining and sentiment classification studies in three non-English languages to find the classification methods and the efficiency of each algorithm used in these methods. It is found that most of the research conducted for non-English has followed the methods used in the English language with onlylimited usage of language specific properties, such as morphological variations. The application domains seem to be restricted to particular fields and significantly less research has been conducted in cross domains. Keywords—Natural Language processing, Text mining, Machine Learning.
机译:在过去的十年中,对英语的观点进行了许多观点挖掘和情感分类研究。但是,非英语文本意见的工作量非常有限。在本文中,我们调查了三种非英语语言的意见挖掘和情感分类研究,以发现分类方法以及这些方法中使用的每种算法的效率。发现大多数针对非英语的研究都遵循了英语中使用的方法,并且仅有限地使用了特定于语言的特性,例如形态变异。应用领域似乎仅限于特定领域,并且在跨领域中进行的研究明显更少。关键字-自然语言处理,文本挖掘,机器学习。

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