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Recovery of the Opinions Through the Specificities of Documents Text

机译:通过文件文本的特殊性恢复意见

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With the explosive growth of textual data from social media (social networks, forums, and blogs), the exploitation of these new sources of information has become crucial. Our work focuses on the sentiment analysis in this context of social media. To identify sentiments from messages, original text mining techniques must be proposed. This article presents a new method that integrates semantic and lexical knowledge for sentiment analysis. The proposed approach gives significant weight to the “sentiment words” for a classification task. Our study focuses on the 88milSMS corpus to highlight the specific characteristics of SMS data in the context of social media.
机译:随着来自社交媒体(社交网络,论坛和博客)的文本数据的爆炸性增长,利用这些新的信息源已变得至关重要。我们的工作重点是在社交媒体的背景下进行情感分析。为了从消息中识别情感,必须提出原始文本挖掘技术。本文提出了一种新方法,该方法将语义和词汇知识集成在一起以进行情感分析。所提出的方法极大地重视了分类任务的“情感词”。我们的研究集中在88milSMS语料库上,以强调社交媒体环境中SMS数据的特定特征。

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