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FluMapper: an interactive CyberGIS environment for massive location-based social media data analysis

Published: 22 July 2013 Publication History
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  • Abstract

    Social media, such as social network (e.g., Facebook), microblogs (e.g. Twitter) have experienced a spectacular rise in popularity, and attracting hundreds of millions of users generating unprecedented amount of information. Twitter, for example, has rapidly gained approximately 500 million registered users as of 2012, generating 340 million tweets daily. Although each tweet is limited to only 140 characters, the aggregate of millions of tweets may provide a realistic representation of landscapes for a certain topic of interest. Furthermore, with widespread use of location aware mobile devices, users are sharing their whereabouts through social media services. This has resulted in a dramatic increase in volume of spatial data and they are becoming a crucial attribute of social media. These location-based social media thus could provide valuable insights to understanding many geographic phenomena. Recent studies capitalizing on social networking and media data show significant societal impacts, in many areas including infectious disease tracking [1].

    References

    [1]
    Wang, S., Cao, G., Zhang, Z., Zhao, Y., Padmanabhan, A. and Wu, K. 2012. A CyberGIS Environment for Analysis of Location-Based Social Media Data. In: Advanced Location-Based Computing and Services, 2nd Edition, ed. A. K. Hassan and H. Amin, CRC Press.
    [2]
    Ginsberg, J., Mohebbi, M., Patel R., Brammer, L., Smolinski, M., and Brilliant, L. 2008. Detecting influenza epidemics using search engine query data. Nature 457, 1012--1014.
    [3]
    Signorini, A., and Segre, A. 2011. The use of Twitter to track levels of disease activity and public concern in the US during the influenza A H1N1 pandemic. PLoS One, 6(5): e19467.
    [4]
    Shi, X. 2010. Selection of bandwidth type and adjustment side in kernel density estimation over inhomogeneous backgrounds. International Journal of Geographical Information Science, 24: 643--660.
    [5]
    Verbeek, K., Buchin, K., and Speckmann, B. 2011. Flow map layout via spiral trees. IEEE Transactions on Visualization and Computer Graphics, 17: 2536--2544.
    [6]
    Wang, S. 2010. A CyberGIS Framework for the Synthesis of Cyberinfrastructure, GIS, and Spatial Analysis. Annals of the Association of American Geographers, 100(3): 535--557.

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    • (2024)Mapping dynamic human sentiments of heat exposure with location-based social media dataInternational Journal of Geographical Information Science10.1080/13658816.2024.234306338:7(1291-1314)Online publication date: 30-Apr-2024
    • (2019)A review of knowledge discovery process in control and mitigation of avian influenzaAnimal Health Research Reviews10.1017/S1466252319000033(1-11)Online publication date: 16-Sep-2019
    • (2019)Harnessing big data for social justice: An exploration of violence against women-related conversations on TwitterHuman Behavior and Emerging Technologies10.1002/hbe2.1601:3(269-279)Online publication date: 26-Jul-2019
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    Published In

    cover image ACM Other conferences
    XSEDE '13: Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery
    July 2013
    433 pages
    ISBN:9781450321709
    DOI:10.1145/2484762
    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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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 July 2013

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    Author Tags

    1. CyberGIS
    2. FluMapper
    3. exploratory spatial data analysis
    4. flow mapping
    5. kernel density estimation

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    Overall Acceptance Rate 129 of 190 submissions, 68%

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    • (2024)Mapping dynamic human sentiments of heat exposure with location-based social media dataInternational Journal of Geographical Information Science10.1080/13658816.2024.234306338:7(1291-1314)Online publication date: 30-Apr-2024
    • (2019)A review of knowledge discovery process in control and mitigation of avian influenzaAnimal Health Research Reviews10.1017/S1466252319000033(1-11)Online publication date: 16-Sep-2019
    • (2019)Harnessing big data for social justice: An exploration of violence against women-related conversations on TwitterHuman Behavior and Emerging Technologies10.1002/hbe2.1601:3(269-279)Online publication date: 26-Jul-2019
    • (2018)Using Eye Tracking to Evaluate the Usability of Flow MapsISPRS International Journal of Geo-Information10.3390/ijgi70702817:7(281)Online publication date: 21-Jul-2018
    • (2018)Social Media Modeling of Human Behavior in Natural EmergenciesProceedings of the Practice and Experience on Advanced Research Computing: Seamless Creativity10.1145/3219104.3219140(1-8)Online publication date: 22-Jul-2018
    • (2018)Social Information Services: A Service Oriented Analysis of Social MediaWeb Services – ICWS 201810.1007/978-3-319-94289-6_17(263-279)Online publication date: 19-Jun-2018
    • (2018)Networks in GeographyEncyclopedia of Social Network Analysis and Mining10.1007/978-1-4939-7131-2_77(1584-1588)Online publication date: 12-Jun-2018
    • (2017)Networks in GeographyEncyclopedia of Social Network Analysis and Mining10.1007/978-1-4614-7163-9_77-1(1-5)Online publication date: 14-Aug-2017
    • (2016)Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics ApproachISPRS International Journal of Geo-Information10.3390/ijgi51001875:10(187)Online publication date: 10-Oct-2016
    • (2016)Big Data and cloud computing: innovation opportunities and challengesInternational Journal of Digital Earth10.1080/17538947.2016.123977110:1(13-53)Online publication date: 3-Nov-2016
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