Abstract
The study is about citizens opinions on student loans by analyzing Twitter reactions to Bidens student loan cancellation project using the machine-driven classification of open-ended response (MDCOR) and found it saved research time, increased efficiency, and ensured authenticity and objectivity of data. After putting data into the application, we found that using five analysis topics is appropriate. The topics content can be predicted by seeking the relevant word for each case. The analysis of five issues related to student loans shows mixed opinions about the impact of loan forgiveness, with some key terms such as predatory and donation being significant. At the same time, some topics are not directly related to the issue.
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