HIV messaging on Twitter: an analysis of current practice and data-driven recommendations

Area of Science:

• Public Health
• Social Media Analysis
• Health Communication

Background:

• Social media platforms are increasingly vital for disseminating public health information, including HIV prevention, testing, and treatment campaigns.
• Understanding message retransmission dynamics is crucial for optimizing the reach and impact of online health initiatives.

Purpose of the Study:

• To identify factors influencing the spread of HIV-related messages on social media.
• To develop data-driven recommendations for enhancing online HIV messaging strategies.

Main Methods:

• Analysis of 20,201 HIV-related tweets from 37 HIV experts posted between 2010 and 2017.
• Utilized machine learning to identify potential predictors of message retransmission.
• Employed multilevel negative binomial models for statistical analysis.

Main Results:

• Fear-related language, message length, and the inclusion of images (photos, GIFs, videos) were strong predictors of retweet counts.
• These factors influenced message spread regardless of whether the content was originally authored by HIV experts or retransmitted by them from non-expert sources.
• Fear appeals and structural message characteristics significantly affect the virality of HIV information online.

Conclusions:

• Fear appeals and structural elements like message length and image inclusion are key drivers of HIV message dissemination on Twitter.
• Findings support the development of evidence-based social media guidelines for public health organizations.
• Recommendations are provided to enhance the spread of critical HIV information through social media channels.