{"title":"Automatic Annotation of Disposition Counts in News Articles.","authors":"Simon Rodier, Dave Carter","doi":"10.3233/SHTI250502","DOIUrl":null,"url":null,"abstract":"<p><p>News media aggregate and report disposition counts during crises: how many people are affected, suspected affected, have died, and have recovered or been recovered; and they tend to do so in a timely and trustworthy manner. We present and evaluate a method for identifying these counts in unstructured natural language text, supporting downstream tasks such as automatic creation of epidemic curves.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"327 ","pages":"906-907"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in health technology and informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/SHTI250502","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
News media aggregate and report disposition counts during crises: how many people are affected, suspected affected, have died, and have recovered or been recovered; and they tend to do so in a timely and trustworthy manner. We present and evaluate a method for identifying these counts in unstructured natural language text, supporting downstream tasks such as automatic creation of epidemic curves.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
