Observation of public sentiment toward human papillomavirus vaccination on Twitter

Abstract

Background: Although human papillomavirus (HPV) is a vaccine-preventable illness, many individuals continue to resist vaccination for themselves and their children. We aimed to systematically analyze Twitter messages to obtain a unique view into public sentiment around HPV vaccination. Methods: We developed a Python-based tool to collect one week of live tweets from February 7–13, 2015 using Twitter’s automated programming interface. We retrieved data related to the HPV vaccine via 22 purposefully-selected key search terms. We developed a codebook using a hybrid approach that involved both a grounded theory approach and the addition of several key important codes based on prior work. Two trained coders independently coded tweets, and interrater reliability was compared using Gwet’s AC1. Results: We collected 20,408 usable tweets. To maintain feasibility, we used a computerized random generator to obtain a sub-sample of 2,000 of these tweets for in-depth qualitative coding. The four categories that accounted for the largest proportion of tweets included news and media coverage of current events related to the HPV vaccine, discussion of possible associations between receiving the vaccine and sexual behavior, safety of the vaccine, and effectiveness of the vaccine. Multiple inaccurate myths surrounding the vaccine, such as the misconception that it is only appropriate for females, were noted. Conclusions: Examination of Twitter chatter around HPV vaccination offers valuable insights, particularly into barriers around vaccination. It would be valuable to develop interventions aimed at countering misinformation promoted on this medium and augmenting valuable information found on it.