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Idioms are extensively used in everyday language. They carry a metaphorical sense that makes their comprehension difficult as their meaning cannot be deduced from the meaning of their constituent parts. They pose a challenge for Natural language processing (NLP) applications like machine translation, information retrieval and question answering as their translation and meaning needs to be derived...
There are many challenges for sentiment classification of user-generated content (UGC) on social media platforms such as micro-blogs. Context dependence, which has been the most challenging problem, is focused on in this paper, and a novel semi-supervised framework is proposed to address the problem. By dividing the feature space of sentiment classification into two parts including the general features...
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