Here are several current research projects. I encourage you to reach out if you are interested in working with me as most of my work is collaborative in nature. This includes projects that are not listed here, and I am open to other ideas.
Longitudinal changes associated with health communication discourse: Structural and temporal features
How does communication about health issues change over time and how can we model patterns of discourse and structural features depending on the platform? My work in this area examines how communication evolves, particularly examining health risks or chronic issues, such as vaccine hesitancy, cardiovascular disease, chronic health issues (e.g., IBD). In several cases, many of these issues are disparities in rural or underserved communities, making it a challenge to understand how cues, nonliteral language, and other patterns evolve over time, and how that can inform our understanding of disclosure and sense making about health.
I’m also interested in interpersonal interactions and organizational structure surrounding online discourse in health issues looking at large data sets. I welcome collaborators on these projects, particularly if you have an interest or expertise in python, R, or other programming skills. We offer training and courses here in CCIS at UA that can also help you develop these skills.
- Future research that I am interested in involves seeking the emotional appeals that individuals share in online platforms, the language they use to express themselves over time, and how emotion and language evolves regarding such issues.
- The interpersonal nature of communication, as well as individual organizational units (e.g., Musaev, Britt, et al., 2019) is work that I seek to expand upon in this line of inquiry. Scholars and students who are interested in interpersonal or organizational communication, computer science, public health, and many other areas might be interested in these projects.
- I’m interested in examining behaviors in communities dedicated to rare diseases or those not readily understood, as they are either personally relevant to me (and thus, I either have some experience with them in a capacity, lending myself some modicum of credibility).
Representative Articles (some are more methodologically relevant; others are topically):
Britt, B. C., & Britt, R. K. (2020). From waifus to whales: The evolution of discourse in a mobile game-based competitive community of practice. Mobile Media & Communication. doi: 10.1177/2050157920934509
Britt, R. K., & Englebert, A. M. (2019). Experiences of patients living with inflammatory bowel disease in rural communities. Qualitative Research in Medicine and Healthcare, 3, 40-46. doi: 10.4081/qrmh.2019.7962
Britt, R. K., & Doss, E. F. (2019). Conceptualizing endometriosis in the r/endo subreddit: A text mining and unsupervised analysis of communication. Manuscript presented at the annual conference of the National Communication Association, Baltimore, MD.
Modeling networks of vaccines, pandemics and health and risk communication on Reddit and Twitter
How is risk expressed and how does it thematically evolve as a discursive practice in large groups? To better classify dimensions associated with sentiment in times of crisis (e.g., pandemics and risk) and risk, we can understand the data structure and conduct sentiment analyses, and build network analyses and topic modeling (e.g., latent Dirichlet allocation) to examine intriguing changes that occur.
- My ongoing interests include examining pandemics or risky health situations and how users communicate about information expressed (note: misinformation as well as simply other conversation points) as well as the rhetorical meaning of cues and contexts discussed about sociopolitical issues surrounding health risks expressed.
- How is communication about risk and pandemics historically communicated about on Reddit? We can visualize this data through tools such as ggplot2, tidytext, and LDA, among other approaches.
- What is the sentiment of messages expressed? Qualitatively, what is expressed historically, from the documented origin of a subreddit dedicated to a particular issue, and what events catalyze its activity spikes and might contribute to subsequent discourse?
Britt, B. C., Britt, R. K., Hayes, J. L., Panek, E. T., Maddox, J., & Musaev, A. (2020). Oral healthcare implications of dedicated online communities: A computational content analysis of the r/dentistry subreddit. Health Communication. doi: 10.1080/10410236.2020.1731937
Britt, R. K., Britt, B. C., Panek, E., & Lee, J. (in press). Communication expressed on the COVID-19 subreddit in the midst of a global pandemic. Health Communication.
The future of health communication: Theorizing about the boundaries of models and data complexity
For the past two years, I have worked with theories and models, such as with Wenger’s (1998) community of practice, which has helped to shape my understanding of the formation and maintenance of communities. I have also examined the death of communities online (Britt et al. 2020). I’m currently working on a few projects relating to health communication that involve scraping large data sets of studies relating to several journals to understand how the field has been historically studied, the topics examined and issues that have not been examined– and offer directions and models based on emerging methods used by social scientists. Please reach out if you’d like to collaborate. I’d like to work with fellow experienced scholars and particularly driven and talented graduate students with a passion for health communication.
- I am especially seeking collaborators who would like to work on a project that are interested in theory building as it relates to the way that theory has implications for the future of communication, health, and online communities. As we look to spaces such as Wikipedia and Reddit, and those where we see users contribute to knowledge, how do existing theories hold up, have evolved in light of publications, and what are the next directions?
- In terms of data complexity, I have a special interest in data and the state of the field of communication and social sciences as a whole (with a particular bias towards computational methods and machine learning)— be it survey, interview, conversations, ethnography, among others. How we might critically interrogate the work we do in an era that is increasingly digital, and continue to do work that is meaningful and makes an actual contribution?
Britt, R. K., Franco, C. L., & Jones, N. (2021). A meta-analysis of health communication studies on Reddit. National Communication Association– Health Communication Division.
Britt, B. C., Britt, R. K., Hayes, J. L., & Oh, J. (2021). Continuing a community of practice beyond the death of its domain: Examining the Tales of Link subreddit. Behaviour & Information Technology. doi: 10.1080/0144929X.2020.1797173
Britt, R. K., Maddox, J., Kanthawala, S., & Hayes, J. L. (2020). The impact of mHealth interventions: Improving health outcomes through narratives, mixed methods and data mining. In J. Kim & H. Song, Eds., New Technologies for Health-related Cognitive and Behavioral Changes. Elsevier.
Social media influence and network and content characteristics
How do influencers shape purchasing decisions and reach their audience today? What are the health implications we must consider, and does it vary depending on the platform used? In our recent research, my team found that the network and content characteristics of mega and micro influencers counteracted conventional wisdom. That is, megainfluencers saw high degree centralization across reply, retweet and mention networks, and low betweenness centralization for retweet networks. Microinfluencers tended to play a central role in their reply network.
- Culturally, what are the differences among influencers in this sector, and their impact on their audience? How do audiences respond accordingly?
- Moreover, how does the communication surrounding influencers differ in communities of practice, and does the language used vary depending on the influencer; if so, through what types of language, sentiment, and what catalyzes such changes?
Britt, R. K., Hayes, J., Britt, B. C., & Park, H. (2020). Too big to sell? A computational analysis of network and content characteristics among mega and micro beauty and fashion social media influencers. Journal of Interactive Advertising. doi.org/10.1080/15252019.2020.1763873