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Sentiment Analysis on Unstructured Review

机译:非结构化评论的情感分析

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摘要

Sentiment analysis mainly focuses on subjectivity and polarity detection. Today consumers make buying decision based on the customer's review that is available in some of the online shopping sites like shopclues, fabfurnish, pepperfry, flipkart etc. There are also some of the specific websites which discuss about positive and negative facts of those products that comes to market like reevoo, buzzillions, bizarte, amazon etc. Hence this type of analysis are socially very needed for sellers to undergo market analysis, branding, product penetration, market segmentation and so on. Here, the proposed paper classifies the most identified features using supervised learning method Naive Bayes and determined their positive, negative and neutral polarity distribution.
机译:情感分析主要集中在主观性和极性检测上。如今,消费者根据顾客的评论做出购买决定,这些评论可在某些在线购物网站(如商店线索,工艺,胡椒粉,flipkart等)上找到。还有一些特定的网站讨论有关这些产品的正面和负面事实诸如reevoo,buzzillions,bizarte,amazon等之类的市场。因此,对于卖家来说,进行市场分析,品牌,产品渗透率,市场细分等,在社会上非常需要这种分析。在这里,拟议论文使用监督学习方法朴素贝叶斯分类最识别的特征,并确定它们的正,负和中性极性分布。

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