Tweets were analyzed inductively by a team of four. They first ran through a sample of 50 tweets to code initial categories. Then they refined these categories iteratively. To strengthen the validity of their analysis, they did member checking, memoing, reflexivity, and triangulation of data.

University of California, Berkeley

This was a mixed methods paper, using both quantitative and qualitative analysis.

Emergency Medicine Influencers’ Twitter Use During the COVID-19 Pandemic: A Mixed-methods Analysis Methods

Leibowitz, M. K., Scudder, M. R., McCabe, M., Chan, J. L., Klein, M. R., Trueger, N. S., & McCarthy, D. M. (2021). Emergency Medicine Influencers’ Twitter Use During the COVID-19 Pandemic: A Mixed-methods Analysis. Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health. https://escholarship.org/uc/item/5bq5n5tf 

Emergency Medicine Influencers’ Twitter Use During the COVID-19 Pandemic: A Mixed-methods Analysis

Statistics were reported for the Tweets such as type (original vs quote), number of tweets per week, reach and engagement through number of followers, like, and retweets, and metrics such as retweets and mentions. The Linguistic Inquiry and Word Count (LIWC) program was used to analyze emotional tone and temporal focus of tweets. For emotional tone, the "positive emotion" and "negative emotion" categories were used, with subcategories such as "Anger," "sadness," and "anxiety." For temporal focus, categories of "past focus," "present focus," and "future focus" were used. Groups were not mutually exclusive. 

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