A comparison of language use in pro- and anti-vaccination comments in response to a high profile Facebook post

Background: Vaccinations are important for controlling the spread of disease, yet an increasing number of people are distrustful of vaccines, and choose not to (fully) vaccinate themselves and their children. One proposed contributor to this distrust is anti-vaccination misinformation available on the internet, where people search for and discuss health information. The language people use in these discussions can provide insights into views about vaccination. Methods: Following a prominent Facebook post about childhood vaccination, language used by participants in a comment thread was analysed using LIWC (Linguistic Inquiry and Word Count). Percentage of words used across a number of categories was compared between pro-vaccination, anti-vaccination, and unrelated (control) comments. Results: Both pro- and anti-vaccination comments used more risk-related and causation words, as well as fewer positive emotion words compared to control comments. Anti-vaccine comments were typified by greater analytical thinking, lower authenticity, more body and health references, and a higher percentage of work-related word use in comparison to pro-vaccine comments, plus more money references than control comments. In contrast, pro-vaccination comments were more authentic, somewhat more tentative, and evidenced higher anxiety words, as well as more references to family and social processes when compared to anti-vaccination comments. Conclusion: Although the anti-vaccination stance is not scientifically-based, comments showed evidence of greater analytical thinking, and more references to health and the body. In contrast, pro-vaccination comments demonstrated greater comparative anxiety, with a particular focus on family and social processes. These results may be indicative of the relative salience of these issues and emotions in differing understandings of the benefits and risks of vaccination. Text-based analysis is a potentially useful and ecologically valid tool for assessing perceptions of health issues, and may provide unique information about particular concerns or arguments expressed on social media that could inform future interventions. (C) 2016 Elsevier Ltd. All rights reserved.