{"title":"社交媒体的语义分析","authors":"Seerat Choudhary, Jyoti Godara","doi":"10.1109/ICCS54944.2021.00054","DOIUrl":null,"url":null,"abstract":"Sentiment research on social media provides businesses with a quick and easy way to track public opinion about their brand, business, directors, and other topics. In recent years, a variety of features and approaches for training sentiment classifiers on datasets have been investigated, with mixed results. In this research, we have proposed an approach for detecting emotion in text and predicting sentiment using semantics as extra characteristics for various datasets and a study on present methods for opinion mining like machine learning and lexicon-based methods.","PeriodicalId":340594,"journal":{"name":"2021 International Conference on Computing Sciences (ICCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Semantic Analysis on Social Media\",\"authors\":\"Seerat Choudhary, Jyoti Godara\",\"doi\":\"10.1109/ICCS54944.2021.00054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sentiment research on social media provides businesses with a quick and easy way to track public opinion about their brand, business, directors, and other topics. In recent years, a variety of features and approaches for training sentiment classifiers on datasets have been investigated, with mixed results. In this research, we have proposed an approach for detecting emotion in text and predicting sentiment using semantics as extra characteristics for various datasets and a study on present methods for opinion mining like machine learning and lexicon-based methods.\",\"PeriodicalId\":340594,\"journal\":{\"name\":\"2021 International Conference on Computing Sciences (ICCS)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computing Sciences (ICCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCS54944.2021.00054\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computing Sciences (ICCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCS54944.2021.00054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sentiment research on social media provides businesses with a quick and easy way to track public opinion about their brand, business, directors, and other topics. In recent years, a variety of features and approaches for training sentiment classifiers on datasets have been investigated, with mixed results. In this research, we have proposed an approach for detecting emotion in text and predicting sentiment using semantics as extra characteristics for various datasets and a study on present methods for opinion mining like machine learning and lexicon-based methods.