Treffer: Song Gao: RAPID: Geospatial Modeling of COVID-19 Spread and Risk Communication by Integrating Human Mobility and Social Media Big Data
Title:
Song Gao: RAPID: Geospatial Modeling of COVID-19 Spread and Risk Communication by Integrating Human Mobility and Social Media Big Data
Authors:
Publication Year:
2021
Collection:
Columbia University: Academic Commons
Subject Terms:
Document Type:
Konferenz
conference object
Language:
English
DOI:
10.7916/bjey-j022
Availability:
Accession Number:
edsbas.CAFB255D
Database:
BASE
Weitere Informationen
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. -- 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.