{"title":"A Proposed Sentiment Analysis Model for Product Reviews on Social Media","authors":"Asha Patel, Bhavesh Patel, Meghna Patel","doi":"10.1109/ICAC3N56670.2022.10074561","DOIUrl":null,"url":null,"abstract":"E-commerce, social medias, forums, blogs etc. become more popular among general public. Nowadays people use this social media platforms to recognize \"general public thinking what\" and \"what was their experience\" before buying any product. Internet contains huge amount of user’s data which is available in various form like comments, opinions and reviews regarding various products, services and events. This trend of reading review data from the internet is constantly growing day by day. People’s reviews or opinions which are available on the internet are unstructured. So it creates difficulty at the time of reviewing huge amount of data for both customers and Business Organization to get cumulative result with high rate of accuracy. So extracting and analyzing the useful things from this reviews content becomes challenging task. As a result, customers and Business Organizations need an automated sentiment analysis system. The proposed sentiment analysis model helps customers to take quick decision about any product or services and the Business Organizations to increase the quality of the product by getting clear idea about their product from the customer point of view.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAC3N56670.2022.10074561","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
E-commerce, social medias, forums, blogs etc. become more popular among general public. Nowadays people use this social media platforms to recognize "general public thinking what" and "what was their experience" before buying any product. Internet contains huge amount of user’s data which is available in various form like comments, opinions and reviews regarding various products, services and events. This trend of reading review data from the internet is constantly growing day by day. People’s reviews or opinions which are available on the internet are unstructured. So it creates difficulty at the time of reviewing huge amount of data for both customers and Business Organization to get cumulative result with high rate of accuracy. So extracting and analyzing the useful things from this reviews content becomes challenging task. As a result, customers and Business Organizations need an automated sentiment analysis system. The proposed sentiment analysis model helps customers to take quick decision about any product or services and the Business Organizations to increase the quality of the product by getting clear idea about their product from the customer point of view.