{"title":"基于深度学习的健康谣言检测","authors":"Wei Zhao, Qian Zhan, Yujin Yan","doi":"10.1109/ICCST53801.2021.00092","DOIUrl":null,"url":null,"abstract":"In this paper, we use the open source paddlepaddle framework, choose the LSTM algorithm to build a health rumor detection platform, and train the model through a self-built Chinese health rumor data set, so as to predict whether the social media information is a health type rumor, and provide a theoretical exploration and effective implementation for the automatic judgement of health rumors.","PeriodicalId":222463,"journal":{"name":"2021 International Conference on Culture-oriented Science & Technology (ICCST)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Health rumors detection based on deep learning\",\"authors\":\"Wei Zhao, Qian Zhan, Yujin Yan\",\"doi\":\"10.1109/ICCST53801.2021.00092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we use the open source paddlepaddle framework, choose the LSTM algorithm to build a health rumor detection platform, and train the model through a self-built Chinese health rumor data set, so as to predict whether the social media information is a health type rumor, and provide a theoretical exploration and effective implementation for the automatic judgement of health rumors.\",\"PeriodicalId\":222463,\"journal\":{\"name\":\"2021 International Conference on Culture-oriented Science & Technology (ICCST)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Culture-oriented Science & Technology (ICCST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCST53801.2021.00092\",\"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 Culture-oriented Science & Technology (ICCST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCST53801.2021.00092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we use the open source paddlepaddle framework, choose the LSTM algorithm to build a health rumor detection platform, and train the model through a self-built Chinese health rumor data set, so as to predict whether the social media information is a health type rumor, and provide a theoretical exploration and effective implementation for the automatic judgement of health rumors.