ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic
Over the past few months, there were huge numbers of circulating tweets and discussions about Coronavirus (COVID-19) in the Arab region. It is important for policy makers and many people to identify types of shared tweets to better understand public behavior, topics of interest, requests from govern...
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| creator | Mubarak, Hamdy Hassan, Sabit |
| description | Over the past few months, there were huge numbers of circulating tweets and
discussions about Coronavirus (COVID-19) in the Arab region. It is important
for policy makers and many people to identify types of shared tweets to better
understand public behavior, topics of interest, requests from governments,
sources of tweets, etc. It is also crucial to prevent spreading of rumors and
misinformation about the virus or bad cures. To this end, we present the
largest manually annotated dataset of Arabic tweets related to COVID-19. We
describe annotation guidelines, analyze our dataset and build effective machine
learning and transformer based models for classification. |
| doi_str_mv | 10.48550/arxiv.2012.01462 |
| format | Article |
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discussions about Coronavirus (COVID-19) in the Arab region. It is important
for policy makers and many people to identify types of shared tweets to better
understand public behavior, topics of interest, requests from governments,
sources of tweets, etc. It is also crucial to prevent spreading of rumors and
misinformation about the virus or bad cures. To this end, we present the
largest manually annotated dataset of Arabic tweets related to COVID-19. We
describe annotation guidelines, analyze our dataset and build effective machine
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discussions about Coronavirus (COVID-19) in the Arab region. It is important
for policy makers and many people to identify types of shared tweets to better
understand public behavior, topics of interest, requests from governments,
sources of tweets, etc. It is also crucial to prevent spreading of rumors and
misinformation about the virus or bad cures. To this end, we present the
largest manually annotated dataset of Arabic tweets related to COVID-19. We
describe annotation guidelines, analyze our dataset and build effective machine
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discussions about Coronavirus (COVID-19) in the Arab region. It is important
for policy makers and many people to identify types of shared tweets to better
understand public behavior, topics of interest, requests from governments,
sources of tweets, etc. It is also crucial to prevent spreading of rumors and
misinformation about the virus or bad cures. To this end, we present the
largest manually annotated dataset of Arabic tweets related to COVID-19. We
describe annotation guidelines, analyze our dataset and build effective machine
learning and transformer based models for classification.</abstract><doi>10.48550/arxiv.2012.01462</doi><oa>free_for_read</oa></addata></record> |
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| identifier | DOI: 10.48550/arxiv.2012.01462 |
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| subjects | Computer Science - Computation and Language Computer Science - Social and Information Networks |
| title | ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic |
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