SensePlace2: GeoTwitter analytics support for situational awareness

Alan M. MacEachren, Anuj Jaiswal, Anthony C. Robinson, Scott Pezanowski, Alexander Savelyev, Prasenjit Mitra, Xiao Zhang, Justine Blanford

Research output: Chapter in Book/Report/Conference proceedingConference contribution

311 Scopus citations

Abstract

Geographically-grounded situational awareness (SA) is critical to crisis management and is essential in many other decision making domains that range from infectious disease monitoring, through regional planning, to political campaigning. Social media are becoming an important information input to support situational assessment (to produce awareness) in all domains. Here, we present a geovisual analytics approach to supporting SA for crisis events using one source of social media, Twitter. Specifically, we focus on leveraging explicit and implicit geographic information for tweets, on developing place-time-theme indexing schemes that support overview+detail methods and that scale analytical capabilities to relatively large tweet volumes, and on providing visual interface methods to enable understanding of place, time, and theme components of evolving situations. Our approach is user-centered, using scenario-based design methods that include formal scenarios to guide design and validate implementation as well as a systematic claims analysis to justify design choices and provide a framework for future testing. The work is informed by a structured survey of practitioners and the end product of Phase-I development is demonstrated / validated through implementation in SensePlace2, a map-based, web application initially focused on tweets but extensible to other media.

Original languageEnglish (US)
Title of host publicationVAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings
Pages181-190
Number of pages10
DOIs
StatePublished - 2011
Event2nd IEEE Conference on Visual Analytics Science and Technology 2011, VAST 2011 - Providence, RI, United States
Duration: Oct 23 2011Oct 28 2011

Publication series

NameVAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings

Other

Other2nd IEEE Conference on Visual Analytics Science and Technology 2011, VAST 2011
Country/TerritoryUnited States
CityProvidence, RI
Period10/23/1110/28/11

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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