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

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]; P=.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.

Assessment of the Impact of COVID-19 pandemic on population level interest in Skincare: Evidence from a google trends-based Infodemiology study

“…4,5 Besides, Google Trends also used for monitoring behavioral analysis such as for analyzing the smoking ban in China, incidence analysis of HIV infection from Tweets, and multiple sclerosis (MS) analysis in English-speaking countries. [6][7][8] Several studies have done using Google Trends for monitoring the impact of COVID-19 on public interests-based health parameters such as loss-of-smell in the COVID-19 patients, dental problems associated with "toothache" and "tooth pain" keyword search, rapid declination on total joint arthroplasty (TJA), and increase interest in smoking cessation. [9][10][11][12][13][14] In addition, Google Trends also used for finding the anxiety associated with search queries terms of "face mask" and "wash hands".…”

Automatic Cohort Determination from Twitter for HIV Prevention amongst Black and Hispanic Men

“…We used an existing corpus to train and evaluate our classifier. The corpus is described in a recent study 10 where the authors randomly collected tweets from the 1% of publicly available tweets posted between January 1, 2016 and December 31, 2016. They isolated 6,949 tweets posted by young men living in the US by using existing tools and a list of keywords related to sex and HIV, such as HIV, condoms, or clit.…”

“…Integrating the geographical location of social media users to content-based recruitment is thus valuable. Geolocation data has been used for public health surveillance and has been used in conjunction with temporal, textual, and network data to monitor e-cigarette use 4 , opioid abuse 5,6 , influenza 7 , and HIV-related social media discussions [8][9][10] . However, many of these applications remain largely descriptive, rather than predictive or applied to public health practice.…”

Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing

“…As noticed above, the social networks continue to provide important information on several issues: public opinion and emotions on the COVID pandemics in Twitter posts [ 56 , 57 ], surveillance of illicit sales of COVID medication on Twitter and Instagram [ 58 ], observation of COVID symptoms and disease histories collected from a large population in Reddit [ 59 ], surveillance of emerging epidemiological events [ 32 ], analysis of HIV-related tweets and of their relation to the HIV incidence [ 77 ], analysis of drug use on Twitter [ 78 ], analysis of developmental crisis episodes during early adulthood in social media [ 75 ].…”