ArticleActa de investigacion psicologica2018
Who is Saying What on Twitter: An Analysis of Messages with References to HIV and HIV Risk Behavior.
Article in Acta de investigacion psicologica, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Analytic Methods to Investigate HIV-Related Digital Communication: A Scoping Review.Current HIV/AIDS reports · 2025Article
- Decoding HIV Discourse on Social Media: Large-Scale Analysis of 191,972 Tweets Using Machine Learning, Topic Modeling, and Temporal Analysis.Journal of medical Internet research · 2025Article
- [Sexual health information on social media: a systematic scoping review].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2021Article
- Identifying HIV-related digital social influencers using an iterative deep learning approach.AIDS (London, England) · 2021Article
- Assessment of Beliefs and Attitudes About Statins Posted on Twitter: A Qualitative Study.JAMA network open · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This research aimed to determine the nature of social media discussions about HIV. With the goal of conducting a descriptive analysis, we collected almost 1,000 tweets posted February to September 2015. The sample of tweets included keywords related to HIV or behavioral risk factors (e.g., sex, drug use) and was coded for content (e.g., HIV), behavior change strategies, and message source. Seven percent of tweets concerned HIV/AIDS, which were often referred to as jokes or insults. The majority of tweets coded as behavior change attempts involved attitude change strategies. The majority of the tweets (80%) came from private users (vs. organizations). Different types of sources employed different types of behavior change strategies: For instance, private users, compared to experts or organizations, included more strategies to decrease detrimental attitudes (29% versus 6%,
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.