Sentiment analysis of COVID-19 related social distancing using twitter data based on deep learning
Author:
Funder
Technology Development Plan Project of Henan Province, China
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17011-3.pdf
Reference50 articles.
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3. Yuliana Y (2020) Corona virus diseases (Covid-19): Sebuah tinjauan literatur. Wellness Health Mag 2(1):187–192
4. Block P, Hoffman M, Raabe IJ, Dowd JB, Rahal C, Kashyap R, Mills MC (2020) Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world. Nat Hum Behav 4(6):588–596
5. Sun C, Zhai Z (2020) The efficacy of social distance and ventilation effectiveness in preventing COVID-19 transmission. Sustain Cities Soc 62:102390
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