No time to lie: Examining the identity of pro-vaccination and anti-vaccination supporters through their user-generated content.

OBJECTIVE: The study delves into the social identity of pro-vaccination and anti-vaccination supporters, emphasizing an understanding of the values that shape these distinct identities. Furthermore, the research highlights that user-generated content pertaining to vaccines offers valuable insights into the underlying personal values of both pro-vaccination and anti-vaccination groups.

METHOD: We constructed a textual dataset based on 142,596 tweets. This data have been analyzed in three steps. First, linguistic characteristics of the textual data together with underlying personal values of text creators are identified using the LIWC software. Second, the identified personal values were used as an input for moderation analysis, that examined relationship between personal values and social identity for pro-vaccination and anti-vaccination groups. Finally, an automated in-depth text analysis is conducted in Mathematica to understand the narratives created by both groups.

RESULTS: The study findings indicate that both pro-vaccination and anti-vaccination supporters display characteristics of subcultures with distinct group identities. Consequently, based on the results, there is a need for more tailored public health communication strategies addressing these two groups separately.

CONCLUSIONS: Understanding how users create health-related content based on their personal values is crucial. Acknowledging and appreciating the diverse personal values and identities within different groups in the vaccination discourse can inform health communication efforts, aligning them with the specific values of each group. This targeted communication is vital for effectively conveying relevant peer-reviewed health information amid the abundance of health-related user-generated content.