ArticleGM crops & food2023
GMO discussion on Twitter.
Article in GM crops & food, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 6 citations in OpenAlex.
- Genetically modified organisms and sustainable development goals: A survey of Taiwanese public opinion.PloS one · 2025Article
- The impact of 'framing' in the adoption of GM crops.GM crops & food · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper focuses on analyzing discussions related to Genetically Modified Organisms (GMOs) on Twitter, with a specific focus on the spread of misinformation and conspiracy theories. The authors collected and analyzed 1,048,274 English tweets related to GMOs between January 2020 and December 2022 using the Twitter API. The tweets were subjected to topical and sentiment analysis to identify the prevalent themes and attitudes toward GMOs. 30.92% of the tweets in the observed period were negative, 21.65% were neutral, and 47.43% were positive. The authors identified four clusters of tweets associated with misinformation or conspiracy theories: GMOs and vaccines, GMOs and COVID-19, GMOs and Monsanto, and GMOs and Bill Gates. The findings of this analysis can inform strategies for combating the spread of false information and conspiracies on social media and improve public understanding and trust in GMO technology.
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.