When it came time to code, I found in sampling that there were a couple of patterns which arose in terms of vocabulary and feelings indicated within the data sample. The feelings indicated through the rhetoric chosen was important so qualitative coding was necessary, as this allows researchers to have an understanding of the variety of reasons for the researched behavior (Blackstone 2012). Noticing such patterns brought me to my coding themes which included vaccine side effects, big pharma, vaccine effectiveness, pro-vax, 5G conspiracy theories and vaccine resistance. The coding theme of big pharma consisted of tweets discussing the corruption vaccine manufacturers. While the 5G conspiracy theories theme included tweets which mentioned aspects of the 5G conspiracy theory, that was based on the idea that 5G was connected to the COVID-19 outbreak (Ahmed et al. 2020 ‘“COVID-19 and the Film Your Hospital”’Conspiracy Theory: Social Network Analysis of Twitter Data).
While coding I found that twitter users were not very specific about vaccine side effects which led me to add injury and death as codes to the side effects category. Certain words like injury came up frequently which meant that quantitative coding was necessary, when studying a phenomenon from a large group quantitative coding tends to be helpful (Blackstone 2012). While coding for the effectiveness category, I realized I needed to add more codes such as untested, which were tweets that discussed the lack of testing or information about the vaccine. Furthermore I noticed a pattern of twitter users discussing how the vaccine is ineffective or dangerous for children so I implemented this to my effectiveness coding category. During the process of qualitative coding I found that fear was indicated often among people questioning the effectiveness of the vaccine so I added that to my effectiveness code category. In the case of the pro-vax category I found many tweets implying a sense of gratitude for the vaccine during qualitative coding, so I also added this to the category of pro-vax.