{"title":"基于自然语言处理和机器学习的文本数据情感检测新方法","authors":"Subhodeep Banerjee, Shrivasta Goswami, A. Das, Neeloy Saha, Soumyashree Seth, Sagnik Bhattacharya, Sandip Mandal, Uem Kolkata","doi":"10.15864/ajec.2105","DOIUrl":null,"url":null,"abstract":"\n Abstract - Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content– based classification problem involving concepts from the domains of Natural\n Language Processing as well as Machine Learning. In this paper we are proposing a solution for emotion recognition based on textual data. The emotion expressed in a blog, review or any kind of textual content remains unused until the text is analyzed and the emotion is retrieved from the data.\n It is impossible to analyze the huge amount of data manually and gain information from it.\n","PeriodicalId":245653,"journal":{"name":"American Journal of Electronics & Communication","volume":"225 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Approach for Emotion Detection from Text Data using Natural Language Processing and Machine Learning\",\"authors\":\"Subhodeep Banerjee, Shrivasta Goswami, A. Das, Neeloy Saha, Soumyashree Seth, Sagnik Bhattacharya, Sandip Mandal, Uem Kolkata\",\"doi\":\"10.15864/ajec.2105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Abstract - Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content– based classification problem involving concepts from the domains of Natural\\n Language Processing as well as Machine Learning. In this paper we are proposing a solution for emotion recognition based on textual data. The emotion expressed in a blog, review or any kind of textual content remains unused until the text is analyzed and the emotion is retrieved from the data.\\n It is impossible to analyze the huge amount of data manually and gain information from it.\\n\",\"PeriodicalId\":245653,\"journal\":{\"name\":\"American Journal of Electronics & Communication\",\"volume\":\"225 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Electronics & Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15864/ajec.2105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Electronics & Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15864/ajec.2105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Approach for Emotion Detection from Text Data using Natural Language Processing and Machine Learning
Abstract - Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content– based classification problem involving concepts from the domains of Natural
Language Processing as well as Machine Learning. In this paper we are proposing a solution for emotion recognition based on textual data. The emotion expressed in a blog, review or any kind of textual content remains unused until the text is analyzed and the emotion is retrieved from the data.
It is impossible to analyze the huge amount of data manually and gain information from it.