The current beta-version of the Daily Tracker exist in two implementations, two separate CSVs:
- normalized time [day_1, day_2, day_3, day_x.....] - day_1 == first day after publication, ..., day_x == x day since publication.
- appropriate formatting for survival analysis or most standard statistical analysis
- natural time [2020_01_01, 2020_01_02, ...] - indicates actual dates.
- appropriate formatting for real-event analysis. Say once could add markers for actual events --first U.S. case-- on a time-series
- id_master_1- main_id for Link_Cov_P
- id_master_2- main_id for Link_Cov_P
- id_who- unique_id indicating that the covid article meta-data comes from WHO dataset
- id_wos-unique_id indicating that the covid article meta-data comes from WOS dataset
- id_cord-unique_id indicating that the covid article meta-data comes from CORD-19 dataset
- id_lit-unique_id indicating that the covid article meta-data comes from LitCovid dataset
- id_aca-unique_id indicating that the covid article meta-data comes from Academia.edu dataset
- covid_kw- Dummy variable indicating that a Covid-19 related keywords was found in either the title, the abstract, or the abstract kw
- titles_all- article title
- journal_merged- journal names of Covid-19 Corpus
- day_1 / 2020_1_1-normalized date of publication / naturalized date of publication. Total # of citation(s) received on the day after publication / on January 1st.
- day_2 / 2020_1_2-ibid.
- day_3 /2020_1_3-ibid.
- day_4 /2020_1_4-ibid.
- day_5 /2020_1_5-ibid.
- day_6 /2020_1_6-ibid.
- day_7 /2020_1_7-ibid.
- etc..