Our research is driven by the following question: how can universities and colleges in the United States better deal with the COVID-19 pandemic? We are interested in the impact of reopening methods for classes and housing, resource and information sharing with students, and other important university responsibilities. Following that, we will examine the challenges in the universities’ practices, and why the universities are facing those challenges. This can include student responses to the approaches. Positive case numbers may reflect the effectiveness of the policies and communication. We then explore what can be done to improve these approaches. In summary, our research questions are summarized as follows, RQ1. Are the universities’ COVID-19 policies effective on pandemic control? Which policies are more effective than others? RQ2. Does university communication on policy implementation matter on pandemic control? RQ3. Does students’ perception of university policy impact pandemic control? Most research in COVID-19 literature focuses on policy making – from the federal government, the CDC, state, and local governments – and case prediction. In this study, we attempt to use online social media data to better understand the student perspective of their university’s reopening and COVID-19 prevention measures and its impact on pandemic control. We collected policy information and case numbers from multiple authority resources. And, we created a web crawler to scrape Twitter data related to 250 universities including tweets, retweets, replies, and likes. Based on those tweets, we gauge student sentiment toward their university’s policy and communication. Moreover, we apply a quantitative analysis approach to explore the role of university policy, student perceptions, and their interaction on pandemic control. We believe that the expected result of our work can help universities better understand the student experiences and therefore improve their policy, response, and communication strategies to survive this turbulent period.
Presenters/Authors: Claire Galberg & Mark Cao; other student authors: Brandon Pugh, Yao Luo
Faculty Advisor: Jay Shan, Information Systems & Analytics
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