ArticleOpen forum infectious diseases2022
The Politicization of Ivermectin Tweets During the COVID-19 Pandemic.
Article in Open forum infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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.
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Who cites it
8 citing papers in PubMed.
- Birds of a feather? Mis- and dis-information on the social media platform X related to avian influenza.Antimicrobial stewardship & healthcare epidemiology : ASHE · 2025Article
- A National Discussion of COVID-19 on Twitter.Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2024Article
- Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society.PloS one · 2024Article
- Twitter discussions on breastfeeding during the COVID-19 pandemic.International breastfeeding journal · 2023Article
- Off-label drug use during the COVID-19 pandemic in Africa: topic modelling and sentiment analysis of ivermectin in South Africa and Nigeria as a case study.Journal of the Royal Society, Interface · 2023Article
- Lessons Learned from Ivermectin.Journal of general internal medicine · 2023Article
- The Association of a Geographically Wide Social Media Network on Depression: County-Level Ecological Analysis.Journal of medical Internet research · 2023Article
- Reaching Populations at Risk for HIV Through Targeted Facebook Advertisements: Cost-Consequence Analysis.JMIR formative research · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: We explore the ivermectin discourse and sentiment in the United States with a special focus on political leaning through the social media blogging site Twitter. Methods: We used sentiment analysis and topic modeling to geospatially explore ivermectin Twitter discourse in the United States and compared it to the political leaning of a state based on the 2020 presidential election. Results: All modeled topics were associated with a negative sentiment. Tweets originating from democratic leaning states were more likely to be negative. Conclusions: Real-time analysis of social media content can identify public health concerns and guide timely public health interventions tackling disinformation.
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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.