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

ABSTRACT:

Objectives

Social media messages have been increasingly used in health campaigns about prevention, testing, and treatment of HIV. We identified factors leading to the retransmission of messages from expert social media accounts to create data-driven recommendations for online HIV messaging.

Design and methods

We sampled 20 201 HIV-related tweets (posted between 2010 and 2017) from 37 HIV experts. Potential predictors of retransmission were identified based on prior literature and machine learning methods, and were subsequently analyzed using multilevel negative binomial models.

Results

Fear-related language, longer messages, and including images (e.g. photos, gif, or videos) were the strongest predictors of retweet counts. These findings were similar for messages auth

SUBMITTER: Lohmann S 

PROVIDER: S-EPMC6615455 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature