Paulo Carvalho, Daniel Mendes, Elaine Alves De Carvalho, Alessandro Jatobá
{"title":"Digital Health Surveillance: Usability requirements applied to rumor alerting and monitoring tools","authors":"Paulo Carvalho, Daniel Mendes, Elaine Alves De Carvalho, Alessandro Jatobá","doi":"10.54941/ahfe1003079","DOIUrl":null,"url":null,"abstract":"This article has the objective of associating the contribution of social media to a system for detecting rumors in public health, aiming to provide timely inputs for the Strategic Information and Health Surveillance Response Centers (CIEVS) in their event monitoring activities in health through the capture and analysis of unofficial information (rumors). Through a process based on usability requirements identified with analysts at the Surveillance Centers, messages are captured, stored and subsequently analyzed cooperatively by analysts to detect the existence of a possible event in public health.","PeriodicalId":259265,"journal":{"name":"AHFE International","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AHFE International","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1003079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article has the objective of associating the contribution of social media to a system for detecting rumors in public health, aiming to provide timely inputs for the Strategic Information and Health Surveillance Response Centers (CIEVS) in their event monitoring activities in health through the capture and analysis of unofficial information (rumors). Through a process based on usability requirements identified with analysts at the Surveillance Centers, messages are captured, stored and subsequently analyzed cooperatively by analysts to detect the existence of a possible event in public health.