title: EventRiver: visually exploring text collections with temporal references.
abstract: Many text collections with temporal references, such as news corpora and weblogs, are generated to report and discuss real life events. Thus, event-related tasks, such as detecting real life events that drive the generation of the text documents, tracking event evolutions, and investigating reports and commentaries about events of interest, are important when exploring such text collections. To incorporate and leverage human efforts in conducting such tasks, we propose a novel visual analytics approach named EventRiver. EventRiver integrates event-based automated text analysis and visualization to reveal the events motivating the text generation and the long term stories they construct. On the visualization, users can interactively conduct tasks such as event browsing, tracking, association, and investigation. A working prototype of EventRiver has been implemented for exploring news corpora. A set of case studies, experiments, and a preliminary user test have been conducted to evaluate its effectiveness and efficiency.
authors.affiliation: University of North Carolina, Charlotte, NC, USA.
authors.forename: Dongning
authors.initials: D
authors.lastname: Luo
authors.forename: Jing
authors.initials: J
authors.lastname: Yang
authors.forename: Milos
authors.initials: M
authors.lastname: Krstajic
authors.forename: William
authors.initials: W
authors.lastname: Ribarsky
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Keim
mesh_terms: D016000:Cluster Analysis; D003196:Computer Graphics; D003628:Database Management Systems; D016208:Databases, Factual; D006801:Humans; D008402:Mass Media; D008962:Models, Theoretical; D012660:Semantics; D013997:Time Factors; D014584:User-Computer Interface