Extracting Physical Events from Digital Chatter for Covid-19

Authors

Vikram Nagapudi, ArchBishop Mitty High School,San Jose,USA
Ameeta Agrawal, Portland State UniversityFollow
Nirupama Bulusu, Portland State UniversityFollow

Published In

2021 IEEE International Conference on Smart Computing (SMARTCOMP)

Document Type

Citation

Publication Date

9-2021

Subjects

COVID 19 (Disease) -- United States

Abstract

By June 3, 2021, the US experienced over 33 million total cases of Covid-19, surpassing 592,000 deaths. In response, the Centers for Disease Control and Prevention (CDC) advised masking, social distancing and avoiding mass gatherings. In this work, we seek to automatically identify physical mass gathering events including dates and locations from digital chatter, i.e., social media data. We also study spread and sentiment associated with such large gathering events, finding a moderate negative correlation between large public gatherings, overall sentiment, and reported Covid-19 case numbers post event.

Rights

© Copyright 2021 IEEE - All rights reserved.

Locate the Document

https://doi.org/10.1109/SMARTCOMP52413.2021.00082

DOI

10.1109/SMARTCOMP52413.2021.00082

Persistent Identifier

https://archives.pdx.edu/ds/psu/36643

Publisher

IEEE

Citation Details

Nagapudi, V., Agrawal, A., & Bulusu, N. (2021). Extracting Physical Events from Digital Chatter for Covid-19. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/smartcomp52413.2021.00082