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Sentiment detection from Bangla text using contextual valency analysis

机译:使用上下文效价分析从孟加拉语文本中检测情感

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Sentiment Analysis or opinion mining is an area of important research over the last decade. The basic task in sentiment analysis is classifying the polarity of a given text whether the expressed opinion in the text is positive, negative, or neutral. This paper presents an approach to sentiment assessment from Bangla text using contextual valence analysis. In linguistics valence of a verb is the number of satellite noun phrases with which a verb combines. We have used the WorldNet to get the senses of each word according to its parts of speech and SentiWordNet to get the prior valence (i.e. polarity) of each word. We calculate the total positivity, negativity and neutrality of sentence or document with respect to total sense. We developed our own methodology to calculate the sentiment from Bangla text using valency analysis. Sufficient examples and experiments are presented to describe the methodology.
机译:在过去十年中,情感分析或观点挖掘是一个重要的研究领域。情感分析的基本任务是对给定文本的极性进行分类,无论文本中表达的观点是肯定的,否定的还是中立的。本文提出了一种使用上下文效价分析从孟加拉语文本进行情感评估的方法。在语言学中,动词的价态是动词与之组合的附属名词短语的数量。我们已经使用WorldNet根据单词的词性来获取每个单词的含义,并使用SentiWordNet来获取每个单词的先验价(即极性)。我们计算句子或文档相对于整体意义的总体积极性,否定性和中立性。我们开发了自己的方法,可以使用效价分析从孟加拉语文本中计算出情感。给出了足够的例子和实验来描述该方法。

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