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.