EIDs represent novel and uncertain risks and create unique challenges for the public in understanding the diseases and adopting proper preventative behaviors. EIDs also pose new questions to public health professionals and governmental agencies regarding effectively communicating to the public about such risks. My research is among the first in our field to examine EID-related social media contents through a computational approach and makes unique contributions to Health Communication and Crisis and Risk Communication studies

Using novel machine learning, natural language processing (NLP), social network analysis methods, as well as traditional content analysis, my research examines social media contents about EIDs and EID outbreaks. These studies allow researchers to assess how the public think and feel about EIDs as the outbreak emerges, develops, and disappears and the models developed in these studies will allow researchers to analyze social media contents about other EID outbreaks in real-time in the future. Here are some of completed studies about social media content related to EIDs.

• Tang, L., Liu, W., Thomas, B., Tran, M., Zou, W., Zhang, X., & Zhi, D. (2021). Texas public agencies’ tweets and public engagement during the COVID-19 Pandemic: Natural language processing approach. Journal of Medical Internet Research: Public Health and Surveillance. [Summary] [Full Text]
• Meadows, C.Z., Tang, L., Zou, W. (2022). Managing government legitimacy during the COVID-19 pandemic in China: a semantic network analysis of state-run media Sina Weibo posts. Chinese Journal of Communication. https://doi.org/10.1080/17544750.2021.2016876 [Summary ] [Full text]

The velocity and impact of the spread of misinformation is another characteristic of the information landscape about EIDs. My research examines how misinformation spreads on social media and how people process such misinformation as a function of individual characteristics as well as platform algorithms.

• Zou, W., & Tang, L. (2021). Rumors and processing strategies during the COVID-19 outbreak in China. Public Understanding of Science. 10.1177/0963662520979459. [Summary] [Full Text]
• Tang, L. & Zou, W. (2020). Health information consumption under COVID-19 lockdown: An interview study of residents of Hubei Province, China. Health Communication, 36(1): 74-80. doi: 10.1080/10410236.2020.1847447 [Summary] [Full Text]
• Tang, L., Fujimoto, K., Amith, M., Cunningham, R., Costantini, R.A., York, F., Xiang, G., Boom, J., & Tao, C. (2021). “Down the rabbit hole” of vaccine misinformation on YouTube: Network exposure study. Journal of Medical Internet Research, 23(1): e23262. https://www.jmir.org/2021/1/e23262 [Summary][Full text]