Presentation + Paper
7 June 2024 Data visualization of vaccine hesitancy among African American community in Tuskegee County
Rani Rekha, An'Darius Fergerson, Jennifer Witt, Sai Lakshmi Naidu, Vivian Carter, James Van Haneghan, Prakash Duraisamy
Author Affiliations +
Abstract
In this paper, we determine associations between social media use and beliefs in conspiracy theories and misinformation among African American communities in Tuskegee County. We will study a high community with significant social problems. The primary goal of this work is to visualize how information (both false and accurate) flows through social media, traditional media, and social networks to influence decision-making in rural areas. The second goal is to examine how various other factors moderate this influence. We will examine the impacts of education, age, and other demographics, as well as measure Gigerenzer’s concept of “risk literacy” which examines the accuracy of people’s perceived notions of risk. We will develop our model based on data collected from in-person meetings and town halls, questionnaires, and other information collected to measure peoples’ social media use, social networks, and their beliefs about issues such as the efficacy of COVID vaccines, their trust in the health care system, their beliefs about mental health.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rani Rekha, An'Darius Fergerson, Jennifer Witt, Sai Lakshmi Naidu, Vivian Carter, James Van Haneghan, and Prakash Duraisamy "Data visualization of vaccine hesitancy among African American community in Tuskegee County", Proc. SPIE 13040, Pattern Recognition and Tracking XXXV, 130400G (7 June 2024); https://doi.org/10.1117/12.3015529
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
COVID 19

Data analysis

Data conversion

Web 2.0 technologies

Visualization

Medicine

Data modeling

Back to Top