Table 3.
Number of tweets by continent and category of the codebook.
| America | Europe | Africa | Asia | Oceania | |
|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | n (%) | n (%) | |
| Overall | 10,516 (34.1) | 6,173 (20.03) | 2,249 (7.29) | 3,719 (12.07) | 866 (2.81) |
| Effect assessment | |||||
| No mention | 3,970 (37.8) | 1,755 (28.4) | 741 (53.6) | 766 (20.7) | 297 (34.3) |
| Health benefit | 965 (9.2) | 678 (11.0) | 67 (4.8) | 191 (5.2) | 114 (13.2) |
| Harmful for health | 5,581 (53.1) | 3,740 (60.6) | 575 (41.6) | 2,752 (74.2) | 455 (52.5) |
| User type | |||||
| Health professionals | 5,266 (50.1) | 3,982 (64.5) | 543 (39.3) | 1,754 (47.3) | 483 (55.8) |
| Undetermined | 511 (4.9) | 474 (7.7) | 53 (3.8) | 40 (1.1) | 15 (1.7) |
| Media | 1,332 (12.7) | 611 (9.9) | 358 (25.9) | 264 (7.1) | 52 (6.0) |
| Celebrity | 3,407 (32.4) | 1,106 (17.9) | 429 (31.0) | 1,651 (44.5) | 316 (36.5) |
| Topic | |||||
| Claim | 2,253 (21.4) | 846 (13.7) | 505 (36.5) | 406 (11.0) | 181 (20.9) |
| General information | 4,896 (46.6) | 3,249 (52.6) | 498 (36.0) | 1,359 (36.6) | 368 (42.5) |
| Sale/advertising | 567 (5.4) | 286 (4.6) | 74 (5.4) | 123 (3.3) | 56 (6.5) |
| Testimonials | 2,686 (25.5) | 1,683 (27.3) | 292 (21.1) | 983 (26.5) | 245 (28.3) |
| Trivialization | 114 (1.1) | 109 (1.8) | 14 (1.0) | 838 (22.6) | 16 (1.9) |
| Sentiment related to consumption | |||||
| No mention | 2,951 (28.1) | 1,576 (25.5) | 576 (41.7) | 652 (17.6) | 180 (20.8) |
| Positive | 1,365 (13.0) | 707 (11.5) | 103 (7.5) | 305 (8.2) | 108 (12.5) |
| Negative | 6,200 (59.0) | 3,890 (63.0) | 704 (50.9) | 2,752 (74.2) | 578 (66.7) |
| Consumption type | |||||
| No mention | 9,337 (88.8) | 5,147 (83.4) | 1,275 (92.2) | 3,503 (94.4) | 797 (92.0) |
| Frequent consumption | 1,164 (11.1) | 1,018 (16.5) | 105 (7.6) | 206 (5.6) | 68 (7.9) |
| Occasional/binge consumption | 15 (0.1) | 8 (0.1) | 3 (0.2) | 0 | 1 (0.1) |