{"title":"推特上讨论的预测寨卡病毒预防技术:一项探索性研究","authors":"Soumik Mandal, Manasa Rath, Yiwei Wang, Braja Gopal Patra","doi":"10.1145/3176349.3176874","DOIUrl":null,"url":null,"abstract":"Social media platforms are widely seen as a valuable medium to spread a wide range of information including charitable causes and health awareness. But given the flexibility provided by the social media platforms, it is important to ensure that the right kind of information is delivered to the right audience when needed. The pilot study presented in this paper considered a sample of Zika related tweets that were classified into different prevention techniques. The classification categories were drawn from the guidelines by CDC. Training a logistic regression model on the annotated data we found the accuracy to be 72%. The findings are significant in studying the effectiveness of social media platforms in spreading the right kind of information in time. This in turn can be useful in informing health care officials to take necessary steps with the help of real-time communication for such unfortunate events in future.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Predicting Zika Prevention Techniques Discussed on Twitter: An Exploratory Study\",\"authors\":\"Soumik Mandal, Manasa Rath, Yiwei Wang, Braja Gopal Patra\",\"doi\":\"10.1145/3176349.3176874\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social media platforms are widely seen as a valuable medium to spread a wide range of information including charitable causes and health awareness. But given the flexibility provided by the social media platforms, it is important to ensure that the right kind of information is delivered to the right audience when needed. The pilot study presented in this paper considered a sample of Zika related tweets that were classified into different prevention techniques. The classification categories were drawn from the guidelines by CDC. Training a logistic regression model on the annotated data we found the accuracy to be 72%. The findings are significant in studying the effectiveness of social media platforms in spreading the right kind of information in time. This in turn can be useful in informing health care officials to take necessary steps with the help of real-time communication for such unfortunate events in future.\",\"PeriodicalId\":198379,\"journal\":{\"name\":\"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3176349.3176874\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3176349.3176874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting Zika Prevention Techniques Discussed on Twitter: An Exploratory Study
Social media platforms are widely seen as a valuable medium to spread a wide range of information including charitable causes and health awareness. But given the flexibility provided by the social media platforms, it is important to ensure that the right kind of information is delivered to the right audience when needed. The pilot study presented in this paper considered a sample of Zika related tweets that were classified into different prevention techniques. The classification categories were drawn from the guidelines by CDC. Training a logistic regression model on the annotated data we found the accuracy to be 72%. The findings are significant in studying the effectiveness of social media platforms in spreading the right kind of information in time. This in turn can be useful in informing health care officials to take necessary steps with the help of real-time communication for such unfortunate events in future.