COVID-19

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Please cite the following paper when using this dataset:
N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007
Abstract
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N/A
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People turn to search engines and social media to seek information during
population-level events, such as during civil unrest, disease outbreaks, fires, or flood.
They also tend to participate in discussions and disseminate information and opinions
via social media forums, and smartphone messaging applications. COVID-19 pandemic
was not any different. However, the proper medical awareness and correct information
dissemination is critical during a pandemic. An unprecedented amount of internet traffic
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A dataset contains a total of 578,375 COVID-19 confirmed cases reported in Thailand that were being recorded between 22 January 2021 to 30 July 2021.
Daily reports of the COVID-19 situation in Thailand can be download from https://data.go.th/en/dataset/covid-19-daily.
Resource ID: 87abdf57-7edd-4864-9766-7bb0e87272f9
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In Indian sub-continent COVID-19 second wave started in early March 2021 and its effect was more lethal than the first wave, the confirmed cases and the death rate was higher than in the first wave. Unlike the national lockdown in 2020, this year different states have started imposing lockdown like restrictions spanning April-June 2021. This paper investigates the sentiments of the people using twitter messages during early period of the second wave. Two-weeks data is manually annotated and several machine learning models were built.
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Depressive/Non-depressive tweets between December 2019 and December 2020 originated largely from India and parts of Indian subcontinent. Sentiment Scores alloted using text blob. Tweets are extracted specifically keeping in mind the top 250 most frequently used negative lexicons and positive lexicons accesed using SentiWord and various research publications.
Tweet Amount : 1.4 Lakhs
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