Assessing COVID-19 Impacts on College Students via Automated Processing of Free-form Text
This research provides insights into the changing priorities and mental health of college students during the COVID-19 pandemic, which can inform policy-makers in higher education.
This study analyzed over 9000 free-form text entries from 1451 college students to assess the impact of COVID-19 on their mental health. It found that post-COVID-19, topics like Education became less important while Health became more trending, and negative sentiment significantly increased across all topics.
In this paper, we report experimental results on assessing the impact of COVID-19 on college students by processing free-form texts generated by them. By free-form texts, we mean textual entries posted by college students (enrolled in a four year US college) via an app specifically designed to assess and improve their mental health. Using a dataset comprising of more than 9000 textual entries from 1451 students collected over four months (split between pre and post COVID-19), and established NLP techniques, a) we assess how topics of most interest to student change between pre and post COVID-19, and b) we assess the sentiments that students exhibit in each topic between pre and post COVID-19. Our analysis reveals that topics like Education became noticeably less important to students post COVID-19, while Health became much more trending. We also found that across all topics, negative sentiment among students post COVID-19 was much higher compared to pre-COVID-19. We expect our study to have an impact on policy-makers in higher education across several spectra, including college administrators, teachers, parents, and mental health counselors.