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  • 标题:A Study on Different Approaches of Sentiment Analysis for Big Data
  • 本地全文:下载
  • 作者:Seema Singh ; Praveen Mishra
  • 期刊名称:International Journal of Advances in Engineering and Management
  • 电子版ISSN:2395-5252
  • 出版年度:2021
  • 卷号:3
  • 期号:7
  • 页码:4261-4264
  • DOI:10.35629/5252-030740884093
  • 语种:English
  • 出版社:IJAEM JOURNAL
  • 摘要:Sentiment computing (SA) plays a very vital role in opinion mining and promotes new application opportunities in product reviews and decision making. From a given piece of text, sentiment Analysis does the job of labelling the people’s opinions in three different categories as neutral, positive and negative. The Sentiment Analysis techniques are used in a various departments like ecommerce sites, government organization and entertainment industries. There are various algorithms prevalent for sentiment analysis. The present study compares and contrasts the different techniques of sentiment analysis.
  • 关键词:Sentiment analysis;Big data;Machine Learning;Lexicon-based approach;Hybrid Approach
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