Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Apr 13, 2021
Date Accepted: Sep 8, 2021
Date Submitted to PubMed: Nov 29, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Characteristics and User Engagement of Anti-Vaping Posts on Instagram: Observational Study
ABSTRACT
Background:
Although government agencies acknowledge that the messages about health effects of e-cigarette use should be promoted on social media, how to effectively deliver those health messages is challenging. Instagram is one of the most popular social media platforms among the U.S. youth and young adults, which has been used to educate the public about the potential harm of vaping through anti-vaping posts.
Objective:
We aim to analyze the characteristics and the user engagement of anti-vaping posts on Instagram to provide a guidance for future message development and information delivery.
Methods:
From Instagram 11,322 posts were downloaded by using anti-vaping hashtags, among which 1,025 posts were randomly selected and 500 anti-vaping posts were further identified by hand-coding. The image type, image content and account type of anti-vaping posts were hand-coded, the text information in the caption was explored by topic modeling, and the user engagement of each category was compared.
Results:
Analyses found that the educational/warning-typed anti-vaping images were the most common (50.6%). The average likes of the educational/warning type (15 likes/post) were significantly lower than the catchphrase image type (32.5 likes/post) (p < 0.001). The majority of the anti-vaping posts contained the image content element text (66.4%), followed by the image content element people/person (22%). The images containing people/person elements (32.8 likes/post) had more likes than the images containing other elements (13.8 – 21.1 likes/post). The caption of the anti-vaping Instagram posts covered topics including “Lung health”, “Teen vaping”, “Stop vaping” and “Vaping death cases”. Among the 500 anti-vaping Instagram posts, while most posts were from the anti-vaping community (35.4%) and the personal account types (36.4%), the anti-vaping community account type had the highest average number of posts (1.69 posts/account). However, there was no difference in the number of likes among different account types.
Conclusions:
Multiple features of anti-vaping Instagram posts may be related to the user engagement and perception. Future research should incorporate machine learning methods to identify the most critical features associated with high user engagement in the delivery of health-related information.
Citation
