From: Using semantic clustering to support situation awareness on Twitter: the case of world views
 | S1: k-means clustering with cosine similarity |
---|---|
D1: Paddington | C1.1.1: Run, Unable, Follow |
C1.1.2: Station, Tube, @DailyMirror | |
C1.1.3: Closed, Breaking, Jump, Threatening | |
D2: Boston | C1.2.1: Continued, Crossed, Finish, Line |
C1.2.2: Arrested, @BostonGlobe, Terror | |
C1.2.3: Eludes, Shuts, Hunt | |
D3: Ivory Coast | C1.3.1: Terrorist, @News_Executive, Seaside |
C1.3.2: Guns, Machine, Gunmen, @DailyMirror | |
C1.3.3: Witnesses, Way, @AFP |