Presentations (Communicative Events)

Song Gao: RAPID: Geospatial Modeling of COVID-19 Spread and Risk Communication by Integrating Human Mobility and Social Media Big Data

Gao, Song

This presentation was made by Song Gao, University of Wisconsin-Madison. The presentation’s title is: “RAPID: Geospatial Modeling of COVID-19 Spread and Risk Communication by Integrating Human Mobility and Social Media Big Data.” Funded by NSF Social, Behavioral and Economic Sciences / Division of Behavioral and Cognitive Sciences.

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Every month, the COVID Information Commons Team (along with the Northeast Big Data Innovation Hub) brings together a group of researchers studying wide-ranging aspects of the current pandemic, to share their research and answer questions from our community. The events showcase scientists' ongoing efforts in the fight against COVID-19, including opportunities for collaboration.

Files

  • thumnail for Song Gao, University of Wisconsin-Madison.docx.pdf Song Gao, University of Wisconsin-Madison.docx.pdf application/pdf 68.1 KB Download File
  • thumnail for COVID-19 Research Lightning Talk - Song Gao, University of Wisconsin-Madison.mp4 COVID-19 Research Lightning Talk - Song Gao, University of Wisconsin-Madison.mp4 video/mp4 9.16 MB Play Download File

More About This Work

Academic Units
Northeast Big Data Innovation Hub
Series
COVID-19 Research Lightning Talks
Published Here
March 1, 2022