Selected article for: "International license and recall precision"
Author: Ari Klein; Arjun Magge; Karen O'Connor; Haitao Cai; Davy Weissenbacher; Graciela Gonzalez-Hernandez
Title: A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter
  • Document date: 2020_4_22
    • ID: 8f1arjw1_11
    Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.19.20069948 doi: medRxiv preprint 0.54, recall = 0.52) for the "possible" class, and 0.68 (precision = 0.70, recall = 0.67) when the "probable" and "possible" classes were unified: Figure 1 illustrates the number of detected users from U.S. states who have posted "probable" or "possible" tweets between January 23, 2020 and April 6, 2020. .....
    Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.19.20069948 doi: medRxiv preprint 0.54, recall = 0.52) for the "possible" class, and 0.68 (precision = 0.70, recall = 0.67) when the "probable" and "possible" classes were unified: Figure 1 illustrates the number of detected users from U.S. states who have posted "probable" or "possible" tweets between January 23, 2020 and April 6, 2020. Figure 2 illustrates the cumulative number of users from the top 12 states by report date. . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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