PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Healthcare Informatics Research10.4258/hir.2020.26.3.1752020263175-184Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective AnalysisU Venkatesh, Periyasamy Aravind Gandhihttp://e-hir.org/upload/pdf/hir-2020-26-3-175.pdf, http://e-hir.org/journal/view.php?doi=10.4258/hir.2020.26.3.175, http://e-hir.org/upload/pdf/hir-2020-26-3-175.pdf
Vaccines10.3390/vaccines100101192022101119Using Google Trends to Predict COVID-19 Vaccinations and Monitor Search Behaviours about Vaccines: A Retrospective Analysis of Italian DataAndrea Maugeri, Martina Barchitta, Antonella Agodihttps://www.mdpi.com/2076-393X/10/1/119/pdf
Intelligent Data Analysis for COVID-19 Pandemic10.1007/978-981-16-1574-0_152021331-345Analysis, Modelling and Prediction of COVID-19 Outbreaks Using Machine Learning AlgorithmsV. Ajantha Devihttps://link.springer.com/content/pdf/10.1007/978-981-16-1574-0_15
10.21203/rs.3.rs-27189/v12020On the predictability of COVID-19 in USA: A Google Trends analysisAmaryllis Mavragani, Konstantinos Gillashttps://www.researchsquare.com/article/rs-27189/v1, https://www.researchsquare.com/article/rs-27189/v1.html
Clinical Rheumatology10.1007/s10067-020-05231-z20203982483-2484COVID-19 and Kawasaki disease: an analysis using Google TrendsMrinalini Dey, Sizheng Steven Zhaohttps://link.springer.com/content/pdf/10.1007/s10067-020-05231-z.pdf, https://link.springer.com/article/10.1007/s10067-020-05231-z/fulltext.html, https://link.springer.com/content/pdf/10.1007/s10067-020-05231-z.pdf
English Language Education and Current Trends (ELECT)10.37301/elect.v1i1.3420221-15STUDENTS’ SPEAKING PERFORMANCE ANALYSIS AFTER LEARNING USING GOOGLE MEET AT PANDEMIC ( COVID 19) ERAErnati Ernati, Lesina Mertihttps://elect.bunghatta.ac.id/index.php/elect/article/download/34/38, https://elect.bunghatta.ac.id/index.php/elect/article/download/34/38
Healthcare Informatics Research10.4258/hir.2018.24.4.3002018244300Google Search Trends Predicting Disease Outbreaks: An Analysis from IndiaMadhur Verma, Kamal Kishore, Mukesh Kumar, Aparajita Ravi Sondh, Gaurav Aggarwal, Soundappan Kathirvelhttps://synapse.koreamed.org/pdf/10.4258/hir.2018.24.4.300, https://synapse.koreamed.org/DOIx.php?id=10.4258/hir.2018.24.4.300, https://synapse.koreamed.org/DOIx.php?id=10.4258/hir.2018.24.4.300
Computers, Materials & Continua10.32604/cmc.2022.02071420227111751-1768Prediction of COVID-19 Transmission in the United States Using Google Search TrendsSyed Rizwan Hassan, Ishtiaq Ahmad, Jamel Nebhen, Ateeq Ur Rehman, Muhammad Shafiq, Jin-Ghoo Choihttps://www.techscience.com/cmc/v71n1/45386/pdf
Brain, Behavior, and Immunity10.1016/j.bbi.2020.04.042202088950-951The second worldwide wave of interest in coronavirus since the COVID-19 outbreaks in South Korea, Italy and Iran: A Google Trends studyArtur Strzeleckihttps://api.elsevier.com/content/article/PII:S0889159120305511?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S0889159120305511?httpAccept=text/plain
2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/icrito51393.2021.95961162021Prediction of Covid-19 Cases in India Through Machine Learning Using PythonSandeep Mathur, Krishnasheesh Dattahttp://xplorestaging.ieee.org/ielx7/9596064/9596065/09596116.pdf?arnumber=9596116