ArticleProceedings of the ... ACM Web Science Conference. ACM Web Science Conference2022
Opinions on Homeopathy for COVID-19 on Twitter.
Article in Proceedings of the ... ACM Web Science Conference. ACM Web Science Conference, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed, 3 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Homeopathy is a medical system originating in Germany more than 200 years ago. Based on prior investigations, mainstream health agencies and medical research communities indicate that there is little evidence that homeopathy can be an effective treatment for any specific health condition. However, it continues to be practiced as a popular form of alternative medicine in many countries, even during the ongoing COVID-19 pandemic. In this paper, we mine opinions on homeopathy for COVID-19 expressed in Twitter data. Our experiments are conducted with a dataset of nearly 60K tweets collected during a seven month period ending in July 2020. We first built text classifiers (linear and neural models) to mine opinions on homeopathy (positive, negative, neutral) from tweets using a dataset of 2400 hand-labeled tweets obtaining an average macro F-score of 81.5% for the positive and negative classes. We applied this model to identify opinions from the full dataset. Our results show that the number of unique positive tweets is twice that of the number of unique negative tweets; but when including retweets, there are 23% more negative tweets overall indicating that negative tweets are getting more retweets and better traction on Twitter. Using a word shift graph analysis on the Twitter bios of authors of positive and negative tweets, we observe that opinions on homeopathy appear to be correlated with political/religious ideologies of the authors (e.g., liberal vs nationalist, atheist vs Hindu). To our knowledge, this is the first study to analyze public opinions on homeopathy on any social media platform. Our results surface a tricky landscape for public health agencies as they promote evidence-based therapies and preventative measures for COVID-19.
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.