{"title":"Sentiment Analysis of Customer Feedback on Restaurant Reviews","authors":"Spoorthi C, Dr. Pushpa Ravikumar, Mr. Adarsh M.J","doi":"10.2139/ssrn.3506637","DOIUrl":null,"url":null,"abstract":"Sentiment analysis is a huge volume increasing at a humongous rate everyday which has made it almost impossible to evaluate the data manually. In Social media, twitter, restaurant site people share their opinion as in a huge number of their prevalence. In order to make the process of analyzing the text automatic there are various machine learning techniques that could be applied. The data set is for those enthusiasts who are willing to play with text data and perform sentiment analysis or text classification. The huge quantity of data in textual is generated every day has no value unless processed. The text data problem can be resolute by a choose to take up data mining technique. By using classifier it helps to predict the text data using naïve bayes classifier. This data set consists of actual reviews from real people. So this data set will give a real time experience as to how to deal with textual data.","PeriodicalId":210491,"journal":{"name":"Food Product Development eJournal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Product Development eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3506637","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Sentiment analysis is a huge volume increasing at a humongous rate everyday which has made it almost impossible to evaluate the data manually. In Social media, twitter, restaurant site people share their opinion as in a huge number of their prevalence. In order to make the process of analyzing the text automatic there are various machine learning techniques that could be applied. The data set is for those enthusiasts who are willing to play with text data and perform sentiment analysis or text classification. The huge quantity of data in textual is generated every day has no value unless processed. The text data problem can be resolute by a choose to take up data mining technique. By using classifier it helps to predict the text data using naïve bayes classifier. This data set consists of actual reviews from real people. So this data set will give a real time experience as to how to deal with textual data.