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Twitter Opinion Mining and Boosting Using Sentiment Analysis

机译:推特观点采矿和推动使用情感分析

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Social media has been one of the most efficacious and precise by speakers of public opinion. A strategy which sanctions the utilization and illustration of twitter data to conclude public conviction is discussed in this paper. Sentiments on exclusive entities with diverse strengths and intenseness are stated by public, where these sentiments are strenuously cognate to their personal mood and emotions. To examine the sentiments from natural language texts, addressing various opinions, a lot of methods and lexical resources have been propounded. A path for boosting twitter sentiment classification using various sentiment proportions as meta-level features has been proposed by this article. Analysis of tweets was done on the product iPhone 6.
机译:社交媒体一直是舆论的最有效和最精确的。在本文中讨论了制裁Twitter数据的利用和插图的策略,并在本文中讨论了结论公众定罪。公众表示,具有不同优势和强烈性的独家实体的情绪,这些情绪对他们个人情绪和情感剧烈同切。要从自然语言文本中检查情绪,解决了各种意见,已经提出了许多方法和词汇资源。本文提出了一种使用各种情绪比例提升Twitter情绪分类的路径,作为本文的级别特征。在产品iPhone 6上完成了推文的分析。

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