EDA, preprocessing, and modelling. Different ML & DL projects.
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Twitter discussions and emotions about COVID-19 pandemic: a machine learning approach : https://arxiv.org/ftp/arxiv/papers/2005/2005.12830.pdf
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Public discourse and sentiment during the COVID-19 pandemic: using Latent Dirichlet Allocation for topic modeling on Twitter : https://arxiv.org/ftp/arxiv/papers/2005/2005.08817.pdf
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Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study : https://www.jmir.org/2020/4/e19016/
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GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information : https://arxiv.org/abs/2005.11177 & https://crisisnlp.qcri.org/
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Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set : https://publichealth.jmir.org/2020/2/e19273/
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Social media in times of crisis: Learning from Hurricane Harvey for the coronavirus disease 2019 pandemic response : https://journals.sagepub.com/doi/pdf/10.1177/0268396220929258
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World leaders’ usage of Twitter in response to the COVID-19 pandemic: a content analysis : https://academic.oup.com/jpubhealth/article/42/3/510/5822639
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Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the “Chinese virus” on Twitter: Quantitative Analysis of Social Media Data : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205030/