Association Between HIV-Related Tweets and HIV Incidence in the United States: Infodemiology Study (Preprint)

Author:

Stevens RobinORCID,Bonett StephenORCID,Bannon JacquelineORCID,Chittamuru DeeptiORCID,Slaff BarryORCID,Browne Safa KORCID,Huang SarahORCID,Bauermeister José AORCID

Abstract

BACKGROUND

Adolescents and young adults in the age range of 13-24 years are at the highest risk of developing HIV infections. As social media platforms are extremely popular among youths, researchers can utilize these platforms to curb the HIV epidemic by investigating the associations between the discourses on HIV infections and the epidemiological data of HIV infections.

OBJECTIVE

The goal of this study was to examine how Twitter activity among young men is related to the incidence of HIV infection in the population.

METHODS

We used integrated human-computer techniques to characterize the HIV-related tweets by male adolescents and young male adults (age range: 13-24 years). We identified tweets related to HIV risk and prevention by using natural language processing (NLP). Our NLP algorithm identified 89.1% (2243/2517) relevant tweets, which were manually coded by expert coders. We coded 1577 HIV-prevention tweets and 17.5% (940/5372) of general sex-related tweets (including emojis, gifs, and images), and we achieved reliability with intraclass correlation at 0.80 or higher on key constructs. Bivariate and multivariate analyses were performed to identify the spatial patterns in posting HIV-related tweets as well as the relationships between the tweets and local HIV infection rates.

RESULTS

We analyzed 2517 tweets that were identified as relevant to HIV risk and prevention tags; these tweets were geolocated in 109 counties throughout the United States. After adjusting for region, HIV prevalence, and social disadvantage index, our findings indicated that every 100-tweet increase in HIV-specific tweets per capita from noninstitutional accounts was associated with a multiplicative effect of 0.97 (95% CI [0.94-1.00]; <i>P</i>=.04) on the incidence of HIV infections in the following year in a given county.

CONCLUSIONS

Twitter may serve as a proxy of public behavior related to HIV infections, and the association between the number of HIV-related tweets and HIV infection rates further supports the use of social media for HIV disease prevention.

Publisher

JMIR Publications Inc.

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