{"title":"基于机器学习的社交媒体和情感分析在医疗数据应用中的研究","authors":"R. Meena, V. T. Bai","doi":"10.1109/I-SMAC47947.2019.9032580","DOIUrl":null,"url":null,"abstract":"Due to the rapid advancements in social media, it generates voluminous data in almost different areas of applications. Large amount of potential health related data are being available in large scale in various sources of internet. We explored the small use case of social media data for a particular disease, cancer on three different social media platforms such as google trends, twitter and online forums with the sentiment analysis of the mined text. The study shows that people are more relied on social media for their health related queries and the twitter analysis shows that there is a significant raise in the percentage of positive sentiments in the tweets shared by the organizations and individuals on cancer.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Study on Machine learning based Social Media and Sentiment analysis for medical data applications\",\"authors\":\"R. Meena, V. T. Bai\",\"doi\":\"10.1109/I-SMAC47947.2019.9032580\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the rapid advancements in social media, it generates voluminous data in almost different areas of applications. Large amount of potential health related data are being available in large scale in various sources of internet. We explored the small use case of social media data for a particular disease, cancer on three different social media platforms such as google trends, twitter and online forums with the sentiment analysis of the mined text. The study shows that people are more relied on social media for their health related queries and the twitter analysis shows that there is a significant raise in the percentage of positive sentiments in the tweets shared by the organizations and individuals on cancer.\",\"PeriodicalId\":275791,\"journal\":{\"name\":\"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I-SMAC47947.2019.9032580\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SMAC47947.2019.9032580","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on Machine learning based Social Media and Sentiment analysis for medical data applications
Due to the rapid advancements in social media, it generates voluminous data in almost different areas of applications. Large amount of potential health related data are being available in large scale in various sources of internet. We explored the small use case of social media data for a particular disease, cancer on three different social media platforms such as google trends, twitter and online forums with the sentiment analysis of the mined text. The study shows that people are more relied on social media for their health related queries and the twitter analysis shows that there is a significant raise in the percentage of positive sentiments in the tweets shared by the organizations and individuals on cancer.