Correlation Analysis of Spatio-temporal Arabic COVID-19 Tweets
Author:
Affiliation:
1. Agricultural Research Center, Cairo, Egypt
2. Computer Science Department, University of Sharjah, Sharjah, UAE
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3486633.3491092
Reference24 articles.
1. Monitoring People’s Emotions and Symptoms from Arabic Tweets during the COVID-19 Pandemic
2. Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis
3. COVID-19: Detecting Government Pandemic Measures and Public Concerns from Twitter Arabic Data Using Distributed Machine Learning
4. Hate and offensive speech detection on Arabic social media
5. Detection of Hate Speech in COVID-19–Related Tweets in the Arab Region: Deep Learning and Topic Modeling Approach
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1. Introduction to the Special Issue on Understanding the Spread of COVID-19, Part 2;ACM Transactions on Spatial Algorithms and Systems;2022-11-26
2. SpatialEpi'2022 Workshop Report: The 3rd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology;SIGSPATIAL Special;2022-11
3. Introduction to the Special Issue on Understanding the Spread of COVID-19, Part 1;ACM Transactions on Spatial Algorithms and Systems;2022-09-30
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