{"id":182,"date":"2014-05-13T14:57:06","date_gmt":"2014-05-13T18:57:06","guid":{"rendered":"http:\/\/jhumag.dev.173.166.187.154.xip.io\/?p=182"},"modified":"2014-06-16T12:48:56","modified_gmt":"2014-06-16T16:48:56","slug":"mining-twitters-archives","status":"publish","type":"post","link":"https:\/\/engineering.jhu.edu\/magazine-archive\/2014\/05\/mining-twitters-archives\/","title":{"rendered":"Mining Twitter’s Archives"},"content":{"rendered":"

\"Twitter<\/a>Computer scientist Mark Dredze and his team are on the cutting edge of a movement that has scientists mining publicly available social media data to track public health trends. Recently, Dredze\u2019s team had great success using 140-character Twitter posts to follow the spread of flu nationally, as well as in the five boroughs of New York City.<\/p>\n

While Dredze\u2019s team used their own computers to collect and sort through millions of publicly available tweets, new Twitter Data Grants could change that by providing access to files, dating back to 2006, to select researchers. Such access would allow Dredze\u2019s team to apply the methods they used to track seasonal flu to trends including crime, politics, and responses to natural disasters.<\/p>\n","protected":false},"excerpt":{"rendered":"

Computer scientist Mark Dredze and his team are on the cutting edge of a movement that has scientists mining publicly available social media data to track public health trends. Recently, Dredze\u2019s team had great success using 140-character Twitter posts to follow the spread of flu nationally, as well as in the five boroughs of New…<\/p>\n","protected":false},"author":4,"featured_media":679,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[24],"tags":[],"class_list":["post-182","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-impact","issue-summer-2014"],"acf":[],"yoast_head":"\nMining Twitter's Archives - JHU Engineering Magazine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/engineering.jhu.edu\/magazine-archive\/2014\/05\/mining-twitters-archives\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Mining Twitter's Archives - JHU Engineering Magazine\" \/>\n<meta property=\"og:description\" content=\"Computer scientist Mark Dredze and his team are on the cutting edge of a movement that has scientists mining publicly available social media data to track public health trends. 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