PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Genomics & Informatics10.5808/gi.210112021193e21A biomedically oriented automatically annotated Twitter COVID-19 datasetLuis Alberto Robles Hernandez, Tiffany J. Callahan, Juan M. Bandahttp://genominfo.org/upload/pdf/gi-21011.pdf, http://genominfo.org/journal/view.php?doi=10.5808/gi.21011, http://genominfo.org/upload/pdf/gi-21011.pdf
10.21203/rs.3.rs-95721/v12020An Augmented Multilingual Twitter Dataset for Studying the COVID-19 InfodemicChristian E. Lopez, Caleb Gallemorehttps://www.researchsquare.com/article/rs-95721/v1, https://www.researchsquare.com/article/rs-95721/v1.html
Knowledge-Based Systems10.1016/j.knosys.2016.05.018201610865-78Building a Twitter opinion lexicon from automatically-annotated tweetsFelipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringerhttps://api.elsevier.com/content/article/PII:S095070511630106X?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S095070511630106X?httpAccept=text/plain
IEEE Access10.1109/access.2021.313038320211-1Active Learning Strategy for COVID-19 Annotated DatasetAmril Nazir, Ricky Maulana Fajrihttp://xplorestaging.ieee.org/ielx7/6287639/6514899/09625938.pdf?arnumber=9625938
Data10.3390/data606006420216664A Geo-Tagged COVID-19 Twitter Dataset for 10 North American Metropolitan Areas over a 255-Day PeriodSara Melotte, Mayank Kejriwalhttps://www.mdpi.com/2306-5729/6/6/64/pdf
Social Network Analysis and Mining10.1007/s13278-021-00825-02021111An augmented multilingual Twitter dataset for studying the COVID-19 infodemicChristian E. Lopez, Caleb Gallemorehttps://link.springer.com/content/pdf/10.1007/s13278-021-00825-0.pdf, https://link.springer.com/article/10.1007/s13278-021-00825-0/fulltext.html, https://link.springer.com/content/pdf/10.1007/s13278-021-00825-0.pdf
BMJ10.1136/bmj.m13812020m1381Covid-19: doctors’ visas are automatically extended for one yearAbi Rimmerhttp://data.bmj.org/tdm/10.1136/bmj.m1381, https://syndication.highwire.org/content/doi/10.1136/bmj.m1381
Advances in Intelligent Systems and Computing10.1007/978-3-030-57796-4_252020256-268COVID-19-FAKES: A Twitter (Arabic/English) Dataset for Detecting Misleading Information on COVID-19Mohamed K. Elhadad, Kin Fun Li, Fayez Gebalihttps://link.springer.com/content/pdf/10.1007/978-3-030-57796-4_25
InterConf10.51582/interconf.19-20.08.2021.0152021158-164LANGUAGE OF CORONA-TWITTER: COVID-19 NEOLOGISMSAnna Orel, Yuliia Vasikhttps://ojs.ukrlogos.in.ua/index.php/interconf/article/download/14085/12947, https://ojs.ukrlogos.in.ua/index.php/interconf/article/download/14085/12947
HUMAYA: Jurnal Hukum, Humaniora, Masyarakat, dan Budaya10.33830/humaya.v1i1.1802.202120211130-42ANALISIS POSTINGAN DI TWITTER MENGENAI VAKSINASI COVID-19: PERILAKU SOSIAL TERHADAP VAKSINASI COVID-19 GUNA PENCEGAHAN PENULARAN COVID-19 Khoirun Nisa Aulia Sukmanihttp://jurnal.ut.ac.id/index.php/humaya_fhisip/article/download/1802/877, http://jurnal.ut.ac.id/index.php/humaya_fhisip/article/download/1802/877