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Spatio-temporal Event Visualization from a Geo-parsed Microblog Stream

Published: 07 March 2016 Publication History

Abstract

We devised a method of visualizing spatio-temporal events extracted from a geo-parsed microblog stream by using a multi-layered geo-locational word-cloud representation. In our method, real-time geo-parsing geo-locates posts in the stream, in order to recognize words appearing on a user-specified location and time grid as temporal local events. The recognized temporal local events (textit{e.g.}, sports games) are then displayed on a map as multi-layered word-clouds and are then used for finding global events (textit{e.g.}, earthquakes), in order to avoid occlusions among the local and global events. We showed the effectiveness of our method by testing it on real events extracted from our archive of five years worth of Twitter posts.

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Cited By

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  • (2024)Deep Neural Networks for Location Reference Identification From Bilingual Disaster-Related TweetsIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.321370211:1(880-891)Online publication date: Feb-2024
  • (2023)How can text mining improve the explainability of Food security situations?Journal of Intelligent Information Systems10.1007/s10844-023-00832-x62:4(971-994)Online publication date: 11-Dec-2023
  • (2020)Research and Implementation of Network Public Opinion Rrediction SystemJournal of Physics: Conference Series10.1088/1742-6596/1575/1/0120641575(012064)Online publication date: 14-Jul-2020
  • Show More Cited By

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cover image ACM Conferences
IUI '16 Companion: Companion Publication of the 21st International Conference on Intelligent User Interfaces
March 2016
446 pages
ISBN:9781450341400
DOI:10.1145/2876456
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 07 March 2016

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Author Tags

  1. social media
  2. spatio-temporal visualization
  3. text analysis

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IUI '16 Companion Paper Acceptance Rate 49 of 194 submissions, 25%;
Overall Acceptance Rate 746 of 2,811 submissions, 27%

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View all
  • (2024)Deep Neural Networks for Location Reference Identification From Bilingual Disaster-Related TweetsIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.321370211:1(880-891)Online publication date: Feb-2024
  • (2023)How can text mining improve the explainability of Food security situations?Journal of Intelligent Information Systems10.1007/s10844-023-00832-x62:4(971-994)Online publication date: 11-Dec-2023
  • (2020)Research and Implementation of Network Public Opinion Rrediction SystemJournal of Physics: Conference Series10.1088/1742-6596/1575/1/0120641575(012064)Online publication date: 14-Jul-2020
  • (2019)Twitter-based traffic delay detection based on topic propagation analysis using railway network topologyPersonal and Ubiquitous Computing10.1007/s00779-019-01204-523:2(233-247)Online publication date: 1-Apr-2019
  • (2018)Location reference identification from tweets during emergencies: A deep learning approachInternational Journal of Disaster Risk Reduction10.1016/j.ijdrr.2018.10.021Online publication date: Oct-2018
  • (2016)3D Information Visualization for Analyzing Temporal Changes in Social Media ContentsJournal of the Visualization Society of Japan10.3154/jvs.36.141_2136:141(21-26)Online publication date: 2016

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