Table 1.
Description of tweets and Twitter users.
| Variable | Total, n (%) | ||
| Number of raising awareness messages in a tweet | |||
| 0 | 1273 (67.68) | ||
| 1 | 347 (18.45) | ||
| 2 | 149 (7.92) | ||
| 3 | 83 (4.41) | ||
| 4 | 25 (1.33) | ||
| 5 | 4 (0.21) | ||
| Sensitizing tweet | 608 (32.32) | ||
| Incentive to carry out the smear test | 440 (23.39) | ||
| Reminder of smear test preventive nature | 217 (11.54) | ||
| Allusion to the mortality or morbidity of cervical cancer | 134 (7.12) | ||
| Testimony of an experience related to smear test or cervical cancer | 92 (4.89) | ||
| Smear test importance | 63 (3.35) | ||
| Evidence of the number of cervical cancers | 41 (2.18) | ||
| Low incidence of smear test | 27 (1.44) | ||
| Categories of Twitter users | |||
| Unknown | 442 (23.5) | ||
| Nonhealth and nonmedia company | 396 (21.05) | ||
| Health company | 292 (15.52) | ||
| Blogger or YouTuber | 262 (13.93) | ||
| Media company | 240 (12.76) | ||
| Fashion activity | 240 (12.76) | ||
| Marketing activity | 220 (11.70) | ||
| National Health Service | 79 (4.2) | ||
| General public | 77 (4.09) | ||
| Woman who experienced cervical cancer or who had relatives that had experienced cervical cancer | 60 (3.19) | ||
| Health professional | 53 (2.82) | ||
| Woman who experienced an abnormal smear test | 33 (1.75) | ||
| Politician | 12 (0.64) | ||
| Woman who experienced an unspecified cancer or had relatives with a similar status | 6 (0.32) | ||