{"title":"The Today Tendency of Sentiment Classification","authors":"V. Phu, Vo Thi Ngoc Tran","doi":"10.5772/INTECHOPEN.74930","DOIUrl":null,"url":null,"abstract":"Sentiment classification has already been studied for many years because it has had many crucial contributions to many different fields in everyday life, such as in political activi -ties, commodity production, and commercial activities. There have been many kinds of the sentiment analysis such as machine learning approaches, lexicon-based approaches, etc., for many years. The today tendency of the sentiment classification is as follows: (1) Processing many big data sets with shortening execution times (2) Having a high accuracy (3) Integrating flexibly and easily into many small machines or many different approaches. We will present each category in more details.","PeriodicalId":442318,"journal":{"name":"Artificial Intelligence - Emerging Trends and Applications","volume":"84 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence - Emerging Trends and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/INTECHOPEN.74930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Sentiment classification has already been studied for many years because it has had many crucial contributions to many different fields in everyday life, such as in political activi -ties, commodity production, and commercial activities. There have been many kinds of the sentiment analysis such as machine learning approaches, lexicon-based approaches, etc., for many years. The today tendency of the sentiment classification is as follows: (1) Processing many big data sets with shortening execution times (2) Having a high accuracy (3) Integrating flexibly and easily into many small machines or many different approaches. We will present each category in more details.