Table 3 Generator analysis A four-panel...

Table 3

Generator analysis

A four-panel table comparing pre- and post-COVID tweet sources for all, active, visible, and verified users.

The diagram shows a table divided into 4 vertical sections. The section-wise details are as follows: The first section is for “Panel 1: All users”. The first row presents the column headers as: Row 1: Column 1: Panel 1: All users; Column 2: Pre-COVID Vaccine Dataset: Number of Generators; Column 3: Pre-COVID Vaccine Dataset: Number of Tweets; Column 4: Pre-COVID Vaccine Dataset: Number of Accounts; Column 5: Post-COVID Vaccine Dataset: Number of Generators; Column 6: Post-COVID Vaccine Dataset: Number of Tweets; Column 7: Post-COVID Vaccine Dataset: Number of Accounts. The complete table is as follows: Row 2: All users: Twitter Clients; Pre-COVID: Number of Generators: 5 (20 percent); Pre-COVID: Number of Tweets: 371 (87.5 percent); Pre-COVID: Number of Accounts: 522 (93.55 percent); Post-COVID: Number of Generators: 37 (5.70 percent); Post-COVID: Number of Tweets: 536,222 (98.34 percent); Post-COVID: Number of Accounts: 335,525 (98.78 percent). Row 3: All users: 3rd Party Clients: Pre-COVID: Number of Generators: 11 (44 percent); Pre-COVID: Number of Tweets: 36 (8.49 percent); Pre-COVID: Number of Accounts: 21 (3.76 percent); Post-COVID: Number of Generators: 225 (34.67 percent); Post-COVID: Number of Tweets: 4666 (0.86 percent); Post-COVID: Number of Accounts: 1996 (0.59 percent). Row 4: All users: Other Social Network: Pre-COVID: Number of Generators: 2 (8 percent); Pre-COVID: Number of Tweets: 5 (1.18 percent); Pre-COVID: Number of Accounts: 4 (0.72 percent); Post-COVID: Number of Generators: 4 (0.62 percent); Post-COVID: Number of Tweets: 423 (0.08 percent); Post-COVID: Number of Accounts: 306 (0.09 percent). Row 5: All users: Social Bots: Pre-COVID: Number of Generators: 3 (12 percent); Pre-COVID: Number of Tweets: 5 (1.18 percent); Pre-COVID: Number of Accounts: 7 (1.25 percent); Post-COVID: Number of Generators: 211 (32.51 percent); Post-COVID: Number of Tweets: 3,300 (0.61 percent); Post-COVID: Number of Accounts: 1,575 (0.46 percent). Row 6: All users: Other: Pre-COVID: Number of Generators: 4 (16 percent); Pre-COVID: Number of Tweets: 7 (1.65 percent); Pre-COVID: Number of Accounts: 4 (0.72 percent); Post-COVID: Number of Generators: 172 (26.50 percent); Post-COVID: Number of Tweets: 64 (0.12 percent); Post-COVID: Number of Accounts: 261 (0.08 percent). The next section is for “Panel 2: Highly Active Users”. The first row presents the column headers as: Row 1: Column 1: Panel 2: Highly Active Users; Column 2: Pre-COVID Vaccine Dataset: Pro (n equals 100); Column 3: Pre-COVID Vaccine Dataset: Anti (n equals 70); Column 4: Post-COVID Vaccine Dataset: Pro (n equals 100); Column 5: Post-COVID Vaccine Dataset: Anti (n equals 51). The complete table is as follows: Row 2 (Twitter Clients): Pre-COVID Pro: 91 (91 percent); Pre-COVID Anti: 66 (94.29 percent); Post-COVID Pro: 90 (90 percent); Post-COVID Anti: 48 (94.12 percent). Row 3 (3rd Party Clients): Pre-COVID Pro: 7 (7 percent); Pre-COVID Anti: 2 (2.85 percent); Post-COVID Pro: 7 (7 percent); Post-COVID Anti: 1 (1.96 percent). Row 4 (Other Social Network): Pre-COVID Pro: 1 (1 percent); Pre-COVID Anti: 2 (2.85 percent); Post-COVID Pro: 1 (1 percent); Post-COVID Anti: 0 (0 percent). Row 5 (Social Bots): Pre-COVID Pro: 0 (0 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 1 (1 percent); Post-COVID Anti: 2 (3.92 percent). Row 6 (Other): Pre-COVID Pro: 1 (1 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 1 (1 percent); Post-COVID Anti: 0 (0 percent). The next section is for “Panel 3: Highly Visible Users”. The first row presents the column headers as: Row 1: Column 1 Panel 3: Highly Visible Users; Column 2: Pre-COVID Vaccine Dataset: Pro (n equals 100); Column 3: Pre-COVID Vaccine Dataset: Anti (n equals 16); Column 4: Post-COVID Vaccine Dataset: Pro (n equals 100); Column 5: Post-COVID Vaccine Dataset: Anti (n equals 100). The complete table is as follows: Row 2 (Twitter Clients): Pre-COVID Pro: 93 (93 percent); Pre-COVID Anti: 14 (87.5 percent); Post-COVID Pro: 92 (92 percent); Post-COVID Anti: 95 (95 percent). Row 3 (3rd Party Clients): Pre-COVID Pro: 5 (5 percent); Pre-COVID Anti: 2 (12.5 percent); Post-COVID Pro: 6 (6 percent); Post-COVID Anti: 4 (4 percent). Row 4 (Other Social Network): Pre-COVID Pro: 0 (0 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 0 (0 percent); Post-COVID Anti: 0 (0 percent). Row 5 (Social Bots): Pre-COVID Pro: 1 (1 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 2 (2 percent); Post-COVID Anti: 1 (1 percent). Row 6 (Other): Pre-COVID Pro: 1 (1 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 0 (0 percent); Post-COVID Anti: 0 (0 percent). The next section is for “Panel 4: Verified Users”. The first row presents the column headers as: Row 1: Column 1: Panel 4: Verified Users; Column 2: Pre-COVID Vaccine Dataset: Pro (n equals 55); Column 3: Pre-COVID Vaccine Dataset: Anti (n equals 1); Column 4: Post-COVID Vaccine Dataset: Pro (n equals 2,999); Column 5: Post-COVID Vaccine Dataset: Anti (n equals 65). The complete table is as follows: Row 2 (Twitter Clients): Pre-COVID Pro: 50 (90.9 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 2,769 (92.3 percent); Post-COVID Anti: 63 (96.92 percent). Row 3 (3rd Party Clients): Pre-COVID Pro: 5 (9.09 percent); Pre-COVID Anti: 1 (100 percent); Post-COVID Pro: 192 (6.4 percent); Post-COVID Anti: 2 (3.08 percent). Row 4 (Other Social Network): Pre-COVID Pro: 0 (0 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 1 (0.03 percent); Post-COVID Anti: 0 (0 percent). Row 5 (Social Bots): Pre-COVID Pro: 0 (0 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 32 (1.07 percent); Post-COVID Anti: 0 (0 percent). Row 6 (Other): Pre-COVID Pro: 0 (0 percent); Pre-COVID Anti: 0 (0 percent); Post-COVID Pro: 5 (0.17 percent); Post-COVID Anti: 0 (0 percent).

Source(s): Authors’ own work

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