This India-specific COVID-19 tweets dataset has been curated using the large-scale Coronavirus (COVID-19) Tweets Dataset. This dataset contains tweets originating from India during the first week of each of the four phases of nationwide lockdowns initiated by the Government of India. For more information on filtering keywords, please visit the primary dataset page.



This dataset gives a cursory glimpse at the overall sentiment trend of the public discourse regarding the COVID-19 pandemic on Twitter. The live scatter plot of this dataset is available as The Overall Trend block at The trend graph reveals multiple peaks and drops that need further analysis. The n-grams during those peaks and drops can prove beneficial for better understanding the discourse.


Recently, the coronavirus pandemic has made the use of facial masks and respirators common, the former to reduce the likelihood of spreading saliva droplets and the latter as Personal Protective Equipment (PPE). As a result, this caused problems for the existing face detection algorithms. For this reason, and for the implementation of other more sophisticated systems, able to recognize the type of facial mask or respirator and to react given this information, we created the Facial Masks and Respirators Database (FMR-DB).


The dataset links to the survey performed on students and professors of Biological Engineering introductory course, as the Department of Biological Engineering, University of the Republic, Uruguay.


Urban informatics and social geographic computing, spatial and temporal big data processing and spatial measurement, map service and natural language processing.


This dataset has the following data about the COVID-19 pandemic in the State of Maranhão, Brazil:

  • Number of daily cases
  • Number of daily deaths

In addition, this dataset also contains data from Google Trends on some subjects related to the pandemic, related to searches carried out in the State of Maranhão.

The data follows a timeline that begins on March 20, 2020, the date of the first case of COVID-19 in the State of Maranhão, until July 9, 2020.


The last decade faced a number of pandemics [1]. The current outbreak of COVID is creating havoc globally. The daily incidences of COVID-2019 from 11th January 2020 to 9th May 2020 were collected from the official COVID dashboard of world health organization (WHO) [2] , i.e. The data is updated with the population of the countries and further Case fatality rate, Basic Attack Rate (BAR) and Household Secondary Attack Rate (HSAR) are computed for all the countries.


We present GeoCoV19, a large-scale Twitter dataset related to the ongoing COVID-19 pandemic. The dataset has been collected over a period of 90 days from February 1 to May 1, 2020 and consists of more than 524 million multilingual tweets. As the geolocation information is essential for many tasks such as disease tracking and surveillance, we employed a gazetteer-based approach to extract toponyms from user location and tweet content to derive their geolocation information using the Nominatim (Open Street Maps) data at different geolocation granularity levels. In terms of geographical coverage, the dataset spans over 218 countries and 47K cities in the world. The tweets in the dataset are from more than 43 million Twitter users, including around 209K verified accounts. These users posted tweets in 62 different languages.


This dataset is very vast and contains tweets related to COVID-19. There are 226668 unique tweet-ids in the whole dataset that ranges from December 2019 till May 2020 . The keywords that have been used to crawl the tweets are 'corona',  ,  'covid ' , 'sarscov2 ',  'covid19', 'coronavirus '.  For getting the other 33 fields of data drop a mail at "". Twitter doesn't allow public sharing of other details related to tweet data( texts,etc.) so can't upload here.


This dataset is very vast and contains Bengali tweets related to COVID-19. There are 36117 unique tweet-ids in the whole dataset that ranges from December 2019 till May 2020 . The keywords that have been used to crawl the tweets are 'corona',  ,  'covid ' , 'sarscov2 ',  'covid19', 'coronavirus '.  For getting the other 33 fields of data drop a mail at "". Code snippet is given in Documentation file. Sharing Twitter data other than Tweet ids publicly violates Twitter regulation policies.